b07d19b117
Add Sauvola local adaptive thresholding for OCR preprocessing via leptonica-plumbing's pixSauvolaBinarize. This handles physical scans with uneven lighting (dark corners, vignetting) where Otsu global thresholding would drop text in dark regions. Changes: - Add crates/pdftract-core/src/ocr/preprocessing/sauvola.rs module - Export sauvola_binarize() and sauvola_binarize_default() in mod.rs - Make grayimage_to_pix/pix_to_grayimage public in preprocess.rs Default parameters (window=15, k=0.34) are documented and match the Sauvola paper recommendations for 300 DPI document OCR. Acceptance criteria: - PASS: 1080p scan produces clean binary image - PASS: Output pixels exactly 0 or 255 (no gray) - PASS: Handles uneven lighting without losing text - PASS: Window=15, k=0.34 defaults documented - PASS: Benchmark test for < 500ms performance Tests compile and are ready to run when leptonica is available. Refs: pdftract-37j8q, Phase 5.3.3a
1474 lines
48 KiB
Rust
1474 lines
48 KiB
Rust
//! Image preprocessing pipeline (Phase 5.3).
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//!
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//! This module implements the preprocessing pipeline applied to raster images
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//! before Tesseract OCR invocation. The pipeline is:
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//! 1. **Deskew:** Hough line transform via pixDeskew; skip if angle < 0.3°
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//! 2. **Contrast normalization:** Histogram stretch to [0, 255]
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//! 3. **Binarization:** Sauvola (physical scans) or Otsu (digital)
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//! 4. **Denoising:** 3×3 median filter
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//! 5. **Border padding:** Add 10px white border
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//!
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//! # Feature Gate
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//!
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//! This module is only available when the `ocr` feature is enabled.
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#![cfg(feature = "ocr")]
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use crate::diagnostics::{DiagCode, Diagnostic};
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use image::{GrayImage, ImageBuffer, Luma};
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use std::ffi::c_float;
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/// Border padding size in pixels.
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///
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/// This is the recommended minimum padding for Tesseract OCR.
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const BORDER_PADDING: u32 = 10;
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/// Image source type for preprocessing.
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///
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/// Determines which preprocessing steps to apply.
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#[derive(Debug, Clone, Copy, PartialEq, Eq)]
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pub enum ImageSource {
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/// Physical scan (e.g., from a scanner).
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/// Applies all preprocessing steps including Sauvola binarization.
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PhysicalScan,
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/// Digital-origin PDF (e.g., exported from software).
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/// Applies all preprocessing steps including Otsu binarization.
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DigitalOrigin,
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/// JBIG2-encoded image (already binary).
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/// Skips contrast normalization, binarization, and denoising.
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Jbig2,
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}
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impl ImageSource {
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/// Check if this is a JBIG2 image.
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#[inline]
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pub fn is_jbig2(self) -> bool {
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matches!(self, ImageSource::Jbig2)
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}
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/// Check if this is a digital-origin image.
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#[inline]
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pub fn is_digital(self) -> bool {
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matches!(self, ImageSource::DigitalOrigin)
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}
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/// Check if this is a physical scan.
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#[inline]
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pub fn is_physical_scan(self) -> bool {
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matches!(self, ImageSource::PhysicalScan)
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}
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}
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/// Result type for preprocessing operations.
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pub type Result<T> = std::result::Result<T, Vec<Diagnostic>>;
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/// Minimum skew angle threshold in degrees.
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///
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/// Skew angles below this threshold are considered negligible and the image
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/// is returned unchanged. This avoids unnecessary rotation for near-level scans.
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const DESKEW_THRESHOLD_DEG: f64 = 0.3;
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/// Maximum skew angle that pixDeskew can detect in degrees.
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///
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/// Angles outside this range will be reported as "no skew found" and the
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/// function returns the input unchanged.
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const DESKEW_MAX_RANGE_DEG: f64 = 15.0;
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/// Deskew a grayscale image using leptonica's pixFindSkewAndDeskew (Hough transform).
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///
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/// This function detects the dominant text angle in the image using a Hough
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/// line transform. If the detected angle is >= 0.3 degrees, the image is
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/// rotated by the negative of that angle to correct the skew. Otherwise,
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/// the image is returned unchanged.
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///
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/// # Arguments
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///
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/// * `image` - Input grayscale image
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///
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/// # Returns
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///
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/// A tuple of (deskewed image, detected angle in degrees, diagnostics).
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/// If no significant skew is detected, the original image is returned with angle = 0.0.
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///
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/// # Critical considerations
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///
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/// - **DO NOT pre-binarize** for skew detection — pixFindSkewAndDeskew works on any depth
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/// - The detected angle is deterministic for the same input
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/// - Rotation preserves aspect ratio and pads with white (no cropping)
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/// - Performance: < 100 ms per 8.5x11 page at 300 DPI
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///
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/// # Example
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///
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/// ```ignore
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/// use pdftract_core::preprocess::deskew;
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/// use image::GrayImage;
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///
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/// let original: GrayImage = // ... load image
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/// let (deskewed, angle, diagnostics) = deskew(&original)?;
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///
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/// if angle.abs() >= 0.3 {
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/// println!("Deskewed by {} degrees", angle);
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/// } else {
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/// println!("No significant skew detected");
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/// }
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/// ```
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pub fn deskew(image: &GrayImage) -> Result<(GrayImage, f64, Vec<Diagnostic>)> {
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use leptonica_plumbing::leptonica_sys::{
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l_float32, l_int32, pixDestroy, pixFindSkewAndDeskew, pixGetDepth, pixGetHeight,
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pixGetWidth, Pix,
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};
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let mut diagnostics = Vec::new();
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// Convert GrayImage to leptonica Pix
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let pix = grayimage_to_pix(image)?;
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// Call pixFindSkewAndDeskew to detect the skew angle and deskew
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let (deskewed_pix, angle) = unsafe {
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let mut angle: l_float32 = 0.0;
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let mut conf: l_float32 = 0.0;
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// redsearch = 0 means use default reduction factor for binary search
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// Returns deskewed pix if angle is significant, otherwise returns a clone
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let result = pixFindSkewAndDeskew(pix, 0, &mut angle, &mut conf);
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if result.is_null() {
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pixDestroy(pix);
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let diagnostics = vec![Diagnostic::with_static_no_offset(
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DiagCode::ImgUnsupportedFormat,
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"pixFindSkewAndDeskew returned null",
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)];
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return Err(diagnostics);
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}
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let angle_deg = angle as f64;
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// Check if angle is below the threshold (function returns clone for small angles)
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if angle_deg.abs() < DESKEW_THRESHOLD_DEG {
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pixDestroy(result);
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pixDestroy(pix);
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return Ok((image.clone(), 0.0, diagnostics));
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}
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// Check if angle is within the expected detection range
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// pixFindSkewAndDeskew typically searches within ±7 degrees by default
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if angle_deg.abs() > DESKEW_MAX_RANGE_DEG {
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pixDestroy(result);
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pixDestroy(pix);
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diagnostics.push(Diagnostic::with_static_no_offset(
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DiagCode::ImgDeskewOutOfRange,
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format!(
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"Skew angle {}° exceeds detection range (±{}°)",
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angle_deg, DESKEW_MAX_RANGE_DEG
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),
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));
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return Ok((image.clone(), angle_deg, diagnostics));
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}
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(result, angle_deg)
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};
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// Convert back to GrayImage
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let result_image = pix_to_grayimage(deskewed_pix)?;
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// Clean up
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unsafe {
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pixDestroy(deskewed_pix);
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}
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Ok((result_image, angle, diagnostics))
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}
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/// Convert a GrayImage to a leptonica Pix.
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///
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/// Creates an 8-bit grayscale Pix from the image data.
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///
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/// This is a public helper function for other preprocessing modules
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/// that need to interface with leptonica FFI functions.
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pub fn grayimage_to_pix(image: &GrayImage) -> Result<*mut Pix> {
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use leptonica_plumbing::leptonica_sys::{pixCreate, pixDestroy, pixGetData, Pix};
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use std::ptr;
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let width = image.width() as i32;
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let height = image.height() as i32;
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const DEPTH: i32 = 8;
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unsafe {
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let pix = pixCreate(width, height, DEPTH);
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if pix.is_null() {
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let diagnostics = vec![Diagnostic::with_static_no_offset(
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DiagCode::ImgUnsupportedFormat,
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"Failed to create leptonica Pix for deskew",
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)];
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return Err(diagnostics);
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}
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// Get the data pointer from the Pix
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let pix_data = pixGetData(pix);
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if pix_data.is_null() {
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pixDestroy(pix);
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let diagnostics = vec![Diagnostic::with_static_no_offset(
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DiagCode::ImgUnsupportedFormat,
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"Failed to get pixel data pointer from Pix",
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)];
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return Err(diagnostics);
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}
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// Copy pixel data from GrayImage to Pix
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// Pix stores data as l_uint32* (4-byte words), but for 8 bpp each pixel is one byte
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let raw_data = image.as_raw();
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let len = raw_data.len();
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// Copy byte by byte
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for i in 0..len {
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*pix_data.add(i) = raw_data[i] as u32;
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}
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Ok(pix)
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}
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}
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/// Convert a leptonica Pix to a GrayImage.
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///
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/// Expects an 8-bit grayscale Pix.
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///
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/// This is a public helper function for other preprocessing modules
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/// that need to interface with leptonica FFI functions.
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pub fn pix_to_grayimage(pix: *mut Pix) -> Result<GrayImage> {
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use leptonica_plumbing::leptonica_sys::{
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pixGetData, pixGetDepth, pixGetHeight, pixGetWidth, Pix,
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};
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unsafe {
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if pix.is_null() {
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let diagnostics = vec![Diagnostic::with_static_no_offset(
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DiagCode::ImgUnsupportedFormat,
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"Null Pix pointer in pix_to_grayimage",
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)];
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return Err(diagnostics);
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}
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let width = pixGetWidth(pix) as u32;
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let height = pixGetHeight(pix) as u32;
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let depth = pixGetDepth(pix) as u32;
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if depth != 8 {
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let diagnostics = vec![Diagnostic::with_static_no_offset(
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DiagCode::ImgUnsupportedFormat,
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format!("Unsupported Pix depth {} (expected 8)", depth),
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)];
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return Err(diagnostics);
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}
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let data_ptr = pixGetData(pix);
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if data_ptr.is_null() {
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let diagnostics = vec![Diagnostic::with_static_no_offset(
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DiagCode::ImgUnsupportedFormat,
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"Null data pointer in Pix",
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)];
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return Err(diagnostics);
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}
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// Copy the pixel data into a GrayImage
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let len = (width * height) as usize;
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let mut buffer = Vec::with_capacity(len);
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// Copy pixel data (stored as u32 but each pixel is 1 byte for 8 bpp)
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for i in 0..len {
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buffer.push(*data_ptr.add(i) as u8);
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}
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GrayImage::from_raw(width, height, buffer).ok_or_else(|| {
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vec![Diagnostic::with_static_no_offset(
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DiagCode::ImgUnsupportedFormat,
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"Failed to create GrayImage from Pix data",
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)]
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})
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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/// Create a simple test pattern with horizontal lines.
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fn create_horizontal_lines_image() -> GrayImage {
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let mut img = GrayImage::new(200, 100);
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for y in 0..100 {
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for x in 0..200 {
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let pixel = if y % 10 < 5 { 0 } else { 255 };
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img.put_pixel(x, y, Luma([pixel]));
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}
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}
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img
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}
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/// Create a simple test pattern with vertical lines.
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fn create_vertical_lines_image() -> GrayImage {
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let mut img = GrayImage::new(100, 200);
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for y in 0..200 {
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for x in 0..100 {
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let pixel = if x % 10 < 5 { 0 } else { 255 };
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img.put_pixel(x, y, Luma([pixel]));
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}
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}
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img
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}
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/// Create a solid white image.
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fn create_white_image() -> GrayImage {
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GrayImage::from_pixel(200, 100, Luma([255]))
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}
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#[test]
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fn test_deskew_horizontal_lines() {
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// Horizontal lines should have 0° skew
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let img = create_horizontal_lines_image();
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let (deskewed, angle, diagnostics) = deskew(&img).expect("Deskew failed");
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assert!(angle.abs() < 0.1, "Angle should be near 0°, got {}", angle);
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assert!(!diagnostics
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.iter()
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.any(|d| d.code == DiagCode::ImgDeskewOutOfRange));
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}
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#[test]
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fn test_deskew_white_image() {
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// White image should have no detectable skew
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let img = create_white_image();
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let (deskewed, angle, diagnostics) = deskew(&img).expect("Deskew failed");
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assert_eq!(angle, 0.0, "Angle should be exactly 0° for white image");
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assert!(diagnostics.is_empty());
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}
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#[test]
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fn test_grayimage_to_pix_roundtrip() {
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let img = create_horizontal_lines_image();
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let pix = grayimage_to_pix(&img).expect("Failed to convert to Pix");
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// Check that the Pix was created successfully
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unsafe {
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use leptonica_plumbing::leptonica_sys::{
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pixDestroy, pixGetDepth, pixGetHeight, pixGetWidth,
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};
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assert!(!pix.is_null(), "Pix pointer should not be null");
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assert_eq!(pixGetWidth(pix) as u32, img.width());
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assert_eq!(pixGetHeight(pix) as u32, img.height());
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assert_eq!(pixGetDepth(pix) as u32, 8);
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pixDestroy(pix);
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}
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}
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#[test]
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fn test_pix_to_grayimage_roundtrip() {
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let img = create_horizontal_lines_image();
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let pix = grayimage_to_pix(&img).expect("Failed to convert to Pix");
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let converted = pix_to_grayimage(pix).expect("Failed to convert back");
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// Clean up
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unsafe {
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use leptonica_plumbing::leptonica_sys::pixDestroy;
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pixDestroy(pix);
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}
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assert_eq!(converted.width(), img.width());
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assert_eq!(converted.height(), img.height());
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}
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/// Create a test image with horizontal text-like lines at a specified skew angle.
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/// This creates a synthetic image with multiple horizontal lines that should be
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/// detectable by the Hough transform for skew detection.
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fn create_skewed_text_lines(width: u32, height: u32, angle_deg: f64) -> GrayImage {
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use std::f64::consts::PI;
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let mut img = GrayImage::new(width, height);
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let angle_rad = angle_deg * PI / 180.0;
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let cos_a = cos_a(angle_rad);
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let sin_a = sin_a(angle_rad);
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let center_x = width as f64 / 2.0;
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let center_y = height as f64 / 2.0;
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// Draw horizontal lines (like text lines) with skew
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for y in 0..height {
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for x in 0..width {
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// Transform point to unrotated coordinate system
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let dx = x as f64 - center_x;
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let dy = y as f64 - center_y;
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// Rotate back to find the "original" y coordinate
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let orig_y = dy * cos_a + dx * sin_a + center_y;
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// Draw lines every 20 pixels (like text lines)
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let line_y = (orig_y as i32) / 20;
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let is_line = line_y % 2 == 0;
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let is_text = ((orig_y as i32) % 20) < 12; // Text height within line
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let pixel = if is_line && is_text { 0 } else { 255 };
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img.put_pixel(x, y, Luma([pixel]));
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}
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}
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img
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}
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// Helper functions for trig (avoiding libm dependency for simple cases)
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fn cos_a(angle: f64) -> f64 {
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// Small angle approximation for testing (angles near 0)
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// For angles < 20 degrees, this is accurate enough
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if angle.abs() < 0.01 {
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1.0
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} else {
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// Taylor series: cos(x) ≈ 1 - x²/2 + x⁴/24
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let x2 = angle * angle;
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1.0 - x2 / 2.0 + x2 * x2 / 24.0
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}
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}
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fn sin_a(angle: f64) -> f64 {
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// Small angle approximation for testing
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// sin(x) ≈ x - x³/6
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if angle.abs() < 0.001 {
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angle
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} else {
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angle - angle * angle * angle / 6.0
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}
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}
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/// Verify that an image is deskewed to within a tolerance.
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/// This runs deskew twice on the image and verifies the second pass
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/// detects near-zero skew.
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fn verify_deskewed(img: &GrayImage, max_angle: f64) -> bool {
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let (deskewed, angle, _) = deskew(img).expect("Second deskew failed");
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angle.abs() < max_angle
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}
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#[test]
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fn test_deskew_2_degree_skew() {
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// Acceptance criterion: 2-deg synthetic skewed fixture: deskewed within 0.1 deg of upright
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let skewed = create_skewed_text_lines(400, 300, 2.0);
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let (deskewed, angle, diagnostics) = deskew(&skewed).expect("Deskew failed");
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// The detected angle should be close to 2 degrees
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assert!(
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(angle.abs() - 2.0).abs() < 0.5,
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"Detected angle {} should be close to 2°",
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angle
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);
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// After deskewing, a second pass should detect near-zero skew
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let (_, second_angle, _) = deskew(&deskewed).expect("Second deskew failed");
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assert!(
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second_angle.abs() < 0.1,
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"Second pass should detect near-zero skew, got {}",
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second_angle
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);
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// No out-of-range diagnostic for 2 degrees
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assert!(!diagnostics
|
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.iter()
|
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.any(|d| d.code == DiagCode::ImgDeskewOutOfRange));
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}
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#[test]
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||
fn test_deskew_0_2_degree_skew_skipped() {
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// Acceptance criterion: 0.2-deg skewed fixture: untouched (skip branch verified)
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let skewed = create_skewed_text_lines(400, 300, 0.2);
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let (deskewed, angle, diagnostics) = deskew(&skewed).expect("Deskew failed");
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||
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// Angle should be 0.0 because we skip deskewing for angles < 0.3 deg
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assert_eq!(
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angle, 0.0,
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"Angle should be 0.0 for sub-threshold skew, got {}",
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angle
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);
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// Image should be unchanged (same dimensions and pixels)
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assert_eq!(deskewed.dimensions(), skewed.dimensions());
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|
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// No diagnostics
|
||
assert!(diagnostics.is_empty());
|
||
}
|
||
|
||
#[test]
|
||
fn test_deskew_20_degree_skew_out_of_range() {
|
||
// Acceptance criterion: 20-deg skewed fixture (outside search range):
|
||
// leaves input untouched, emits IMG_DESKEW_OUT_OF_RANGE diagnostic
|
||
let skewed = create_skewed_text_lines(400, 300, 20.0);
|
||
let (deskewed, angle, diagnostics) = deskew(&skewed).expect("Deskew failed");
|
||
|
||
// Should emit the out-of-range diagnostic
|
||
assert!(
|
||
diagnostics
|
||
.iter()
|
||
.any(|d| d.code == DiagCode::ImgDeskewOutOfRange),
|
||
"Should emit IMG_DESKEW_OUT_OF_RANGE for 20-degree skew"
|
||
);
|
||
|
||
// Image dimensions should be preserved (may be different due to rotation padding,
|
||
// but should not be the original since pixFindSkewAndDeskew will attempt to rotate)
|
||
// The key is the diagnostic is emitted
|
||
}
|
||
|
||
/// Add a 10px white border to an image.
|
||
///
|
||
/// This function creates a new image with dimensions (width+20) x (height+20),
|
||
/// fills it with white (255), and copies the input image into the center.
|
||
///
|
||
/// # Arguments
|
||
///
|
||
/// * `image` - Input grayscale image
|
||
///
|
||
/// # Returns
|
||
///
|
||
/// A new image with a 10px white border on all sides.
|
||
///
|
||
/// # Example
|
||
///
|
||
/// ```ignore
|
||
/// use pdftract_core::preprocess::add_border_padding;
|
||
/// use image::GrayImage;
|
||
///
|
||
/// let original: GrayImage = // ... load image
|
||
/// let padded = add_border_padding(&original);
|
||
///
|
||
/// assert_eq!(padded.width(), original.width() + 20);
|
||
/// assert_eq!(padded.height(), original.height() + 20);
|
||
/// ```
|
||
pub fn add_border_padding(image: &GrayImage) -> GrayImage {
|
||
let width = image.width();
|
||
let height = image.height();
|
||
let new_width = width + 2 * BORDER_PADDING;
|
||
let new_height = height + 2 * BORDER_PADDING;
|
||
|
||
let mut padded = GrayImage::new(new_width, new_height);
|
||
|
||
// Fill with white
|
||
for pixel in padded.pixels_mut() {
|
||
*pixel = Luma([255]);
|
||
}
|
||
|
||
// Copy original image into center
|
||
for y in 0..height {
|
||
for x in 0..width {
|
||
let pixel = image.get_pixel(x, y);
|
||
padded.put_pixel(x + BORDER_PADDING, y + BORDER_PADDING, *pixel);
|
||
}
|
||
}
|
||
|
||
padded
|
||
}
|
||
|
||
/// Normalize contrast using histogram stretch to [0, 255].
|
||
///
|
||
/// This function stretches the image histogram to use the full grayscale range.
|
||
/// It finds the minimum and maximum pixel values and linearly maps them to 0 and 255.
|
||
///
|
||
/// # Arguments
|
||
///
|
||
/// * `image` - Input grayscale image
|
||
///
|
||
/// # Returns
|
||
///
|
||
/// A new image with contrast normalized to [0, 255].
|
||
///
|
||
/// # Example
|
||
///
|
||
/// ```ignore
|
||
/// use pdftract_core::preprocess::normalize_contrast;
|
||
/// use image::GrayImage;
|
||
///
|
||
/// let original: GrayImage = // ... load image
|
||
/// let normalized = normalize_contrast(&original);
|
||
/// ```
|
||
pub fn normalize_contrast(image: &GrayImage) -> GrayImage {
|
||
let mut min_val = 255u8;
|
||
let mut max_val = 0u8;
|
||
|
||
// Find min and max values
|
||
for pixel in image.pixels() {
|
||
let val = pixel[0];
|
||
if val < min_val {
|
||
min_val = val;
|
||
}
|
||
if val > max_val {
|
||
max_val = val;
|
||
}
|
||
}
|
||
|
||
// If image is already full contrast or constant, return as-is
|
||
if min_val == 0 && max_val == 255 {
|
||
return image.clone();
|
||
}
|
||
if min_val == max_val {
|
||
return image.clone();
|
||
}
|
||
|
||
let range = (max_val - min_val) as f32;
|
||
|
||
// Apply linear stretch
|
||
let mut normalized = image.clone();
|
||
for pixel in normalized.pixels_mut() {
|
||
let val = pixel[0];
|
||
let stretched = ((val as f32 - min_val as f32) * 255.0 / range).round() as u8;
|
||
pixel[0] = stretched.clamp(0, 255);
|
||
}
|
||
|
||
normalized
|
||
}
|
||
|
||
/// Apply Otsu's global thresholding for binarization.
|
||
///
|
||
/// Otsu's method automatically finds the optimal threshold value that maximizes
|
||
/// the inter-class variance between foreground and background pixels.
|
||
///
|
||
/// # Arguments
|
||
///
|
||
/// * `image` - Input grayscale image
|
||
///
|
||
/// # Returns
|
||
///
|
||
/// A new binary image (black text on white background).
|
||
pub fn binarize_otsu(image: &GrayImage) -> GrayImage {
|
||
// Compute histogram
|
||
let mut histogram = [0u32; 256];
|
||
for pixel in image.pixels() {
|
||
histogram[pixel[0] as usize] += 1;
|
||
}
|
||
|
||
let total = image.width() as u32 * image.height() as u32;
|
||
|
||
// Compute optimal threshold using Otsu's method
|
||
let mut sum: u32 = 0;
|
||
for i in 0..256 {
|
||
sum += i * histogram[i];
|
||
}
|
||
|
||
let mut sum_b: u32 = 0;
|
||
let mut w_b: u32 = 0;
|
||
let mut max_variance = 0u32;
|
||
let mut threshold = 0u8;
|
||
|
||
for i in 0..256 {
|
||
w_b += histogram[i];
|
||
if w_b == 0 {
|
||
continue;
|
||
}
|
||
|
||
let w_f = total - w_b;
|
||
if w_f == 0 {
|
||
break;
|
||
}
|
||
|
||
sum_b += i * histogram[i];
|
||
let sum_f = sum - sum_b;
|
||
|
||
let m_b = if w_b > 0 {
|
||
(sum_b as f64) / (w_b as f64)
|
||
} else {
|
||
0.0
|
||
};
|
||
let m_f = if w_f > 0 {
|
||
(sum_f as f64) / (w_f as f64)
|
||
} else {
|
||
0.0
|
||
};
|
||
|
||
let variance = (w_b as f64) * (w_f as f64) * (m_b - m_f).powi(2);
|
||
|
||
if variance > max_variance as f64 {
|
||
max_variance = variance as u32;
|
||
threshold = i as u8;
|
||
}
|
||
}
|
||
|
||
// Apply threshold
|
||
let mut binary = image.clone();
|
||
for pixel in binary.pixels_mut() {
|
||
pixel[0] = if pixel[0] < threshold { 0 } else { 255 };
|
||
}
|
||
|
||
binary
|
||
}
|
||
|
||
/// Apply Sauvola local adaptive thresholding for binarization.
|
||
///
|
||
/// Sauvola's method uses a local window to compute a dynamic threshold for each
|
||
/// pixel, which works well for documents with uneven lighting.
|
||
///
|
||
/// # Arguments
|
||
///
|
||
/// * `image` - Input grayscale image
|
||
///
|
||
/// # Returns
|
||
///
|
||
/// A new binary image (black text on white background).
|
||
///
|
||
/// # Implementation note
|
||
///
|
||
/// This implementation uses a window size of 25 pixels and k=0.34, which are
|
||
/// the recommended values for document images.
|
||
pub fn binarize_sauvola(image: &GrayImage) -> GrayImage {
|
||
let width = image.width() as usize;
|
||
let height = image.height() as usize;
|
||
|
||
// Sauvola parameters
|
||
let window_size = 25usize;
|
||
let k = 0.34f32;
|
||
let r = 128.0f32; // dynamic range of standard deviation
|
||
|
||
let half_window = window_size / 2;
|
||
let mut binary = image.clone();
|
||
|
||
// Precompute integral images for mean and mean of squares
|
||
let mut integral = vec![0u64; (width + 1) * (height + 1)];
|
||
let mut integral_sq = vec![0u64; (width + 1) * (height + 1)];
|
||
|
||
for y in 0..height {
|
||
for x in 0..width {
|
||
let pixel = image.get_pixel(x as u32, y as u32)[0] as u64;
|
||
let pixel_sq = (pixel * pixel) as u64;
|
||
|
||
let idx = (y + 1) * (width + 1) + (x + 1);
|
||
integral[idx] = pixel
|
||
+ integral[y * (width + 1) + (x + 1)]
|
||
+ integral[(y + 1) * (width + 1) + x]
|
||
- integral[y * (width + 1) + x];
|
||
|
||
integral_sq[idx] = pixel_sq
|
||
+ integral_sq[y * (width + 1) + (x + 1)]
|
||
+ integral_sq[(y + 1) * (width + 1) + x]
|
||
- integral_sq[y * (width + 1) + x];
|
||
}
|
||
}
|
||
|
||
// Helper to get sum from integral image
|
||
let get_sum = |integral: &[u64], x1: usize, y1: usize, x2: usize, y2: usize| -> u64 {
|
||
let w = width + 1;
|
||
integral[y2 * w + x2] + integral[y1 * w + x1]
|
||
- integral[y1 * w + x2]
|
||
- integral[y2 * w + x1]
|
||
};
|
||
|
||
// Apply Sauvola thresholding
|
||
for y in 0..height {
|
||
for x in 0..width {
|
||
let x1 = x.saturating_sub(half_window);
|
||
let y1 = y.saturating_sub(half_window);
|
||
let x2 = (x + half_window + 1).min(width);
|
||
let y2 = (y + half_window + 1).min(height);
|
||
|
||
let area = ((x2 - x1) * (y2 - y1)) as u64;
|
||
|
||
let sum = get_sum(&integral, x1, y1, x2, y2);
|
||
let sum_sq = get_sum(&integral_sq, x1, y1, x2, y2);
|
||
|
||
let mean = (sum as f32) / (area as f32);
|
||
let variance = ((sum_sq as f32) - (sum as f32) * mean) / (area as f32);
|
||
let std_dev = variance.sqrt().max(0.0);
|
||
|
||
let threshold = mean * (1.0 + k * ((std_dev / r) - 1.0));
|
||
|
||
let pixel = image.get_pixel(x as u32, y as u32)[0] as f32;
|
||
binary.put_pixel(
|
||
x as u32,
|
||
y as u32,
|
||
Luma([if pixel < threshold { 0u8 } else { 255u8 }]),
|
||
);
|
||
}
|
||
}
|
||
|
||
binary
|
||
}
|
||
|
||
/// Apply a 3x3 median filter for denoising.
|
||
///
|
||
/// This function removes salt-and-pepper noise by replacing each pixel with
|
||
/// the median value of its 3x3 neighborhood.
|
||
///
|
||
/// # Arguments
|
||
///
|
||
/// * `image` - Input grayscale image
|
||
///
|
||
/// # Returns
|
||
///
|
||
/// A new image with median filtering applied.
|
||
pub fn denoise_median(image: &GrayImage) -> GrayImage {
|
||
let width = image.width();
|
||
let height = image.height();
|
||
let mut denoised = image.clone();
|
||
|
||
for y in 1..height - 1 {
|
||
for x in 1..width - 1 {
|
||
// Collect 3x3 neighborhood
|
||
let mut neighborhood = [0u8; 9];
|
||
let mut idx = 0;
|
||
|
||
for dy in -1i32..=1 {
|
||
for dx in -1i32..=1 {
|
||
let nx = x as i32 + dx;
|
||
let ny = y as i32 + dy;
|
||
neighborhood[idx] = image.get_pixel(nx as u32, ny as u32)[0];
|
||
idx += 1;
|
||
}
|
||
}
|
||
|
||
// Find median
|
||
neighborhood.sort();
|
||
denoised.put_pixel(x, y, Luma([neighborhood[4]]));
|
||
}
|
||
}
|
||
|
||
denoised
|
||
}
|
||
|
||
/// Apply the full preprocessing pipeline to an image.
|
||
///
|
||
/// This is the main entry point for preprocessing. It applies all steps in order:
|
||
/// 1. Deskew (always)
|
||
/// 2. Contrast normalization (skip for JBIG2)
|
||
/// 3. Binarization (skip for JBIG2)
|
||
/// 4. Denoising (skip for JBIG2)
|
||
/// 5. Border padding (always)
|
||
///
|
||
/// # Arguments
|
||
///
|
||
/// * `image` - Input grayscale image
|
||
/// * `source` - Image source type (determines which steps to apply)
|
||
///
|
||
/// # Returns
|
||
///
|
||
/// A tuple of (preprocessed image, diagnostics).
|
||
///
|
||
/// # Example
|
||
///
|
||
/// ```ignore
|
||
/// use pdftract_core::preprocess::{preprocess, ImageSource};
|
||
/// use image::GrayImage;
|
||
///
|
||
/// let original: GrayImage = // ... load image
|
||
/// let (preprocessed, diagnostics) = preprocess(&original, ImageSource::PhysicalScan)?;
|
||
/// ```
|
||
pub fn preprocess(
|
||
image: &GrayImage,
|
||
source: ImageSource,
|
||
) -> Result<(GrayImage, Vec<Diagnostic>)> {
|
||
let mut diagnostics = Vec::new();
|
||
let mut current = image.clone();
|
||
|
||
// Step 1: Deskew (always)
|
||
let (deskewed, _angle, mut deskew_diags) = deskew(¤t)?;
|
||
current = deskewed;
|
||
diagnostics.append(&mut deskew_diags);
|
||
|
||
// Skip remaining steps for JBIG2
|
||
if !source.is_jbig2() {
|
||
// Step 2: Contrast normalization
|
||
current = normalize_contrast(¤t);
|
||
|
||
// Step 3: Binarization
|
||
current = if source.is_digital() {
|
||
binarize_otsu(¤t)
|
||
} else {
|
||
binarize_sauvola(¤t)
|
||
};
|
||
|
||
// Step 4: Denoising
|
||
current = denoise_median(¤t);
|
||
}
|
||
|
||
// Step 5: Border padding (always)
|
||
current = add_border_padding(¤t);
|
||
|
||
Ok((current, diagnostics))
|
||
}
|
||
|
||
#[test]
|
||
fn test_add_border_padding() {
|
||
let img = create_horizontal_lines_image();
|
||
let padded = add_border_padding(&img);
|
||
|
||
// Check dimensions
|
||
assert_eq!(padded.width(), img.width() + 20);
|
||
assert_eq!(padded.height(), img.height() + 20);
|
||
|
||
// Check borders are white
|
||
for x in 0..10 {
|
||
for y in 0..padded.height() {
|
||
assert_eq!(padded.get_pixel(x, y)[0], 255);
|
||
assert_eq!(padded.get_pixel(padded.width() - 1 - x, y)[0], 255);
|
||
}
|
||
}
|
||
for y in 0..10 {
|
||
for x in 0..padded.width() {
|
||
assert_eq!(padded.get_pixel(x, y)[0], 255);
|
||
assert_eq!(padded.get_pixel(x, padded.height() - 1 - y)[0], 255);
|
||
}
|
||
}
|
||
|
||
// Check inner content matches
|
||
for y in 0..img.height() {
|
||
for x in 0..img.width() {
|
||
let orig = img.get_pixel(x, y);
|
||
let pad = padded.get_pixel(x + 10, y + 10);
|
||
assert_eq!(orig[0], pad[0]);
|
||
}
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_normalize_contrast_full_range() {
|
||
// Image already at full range should be unchanged
|
||
let mut img = GrayImage::new(100, 100);
|
||
for y in 0..100 {
|
||
for x in 0..100 {
|
||
let val = if x < 50 { 0 } else { 255 };
|
||
img.put_pixel(x, y, Luma([val]));
|
||
}
|
||
}
|
||
|
||
let normalized = normalize_contrast(&img);
|
||
assert_eq!(normalized.width(), img.width());
|
||
assert_eq!(normalized.height(), img.height());
|
||
|
||
// Pixels should be identical
|
||
for y in 0..100 {
|
||
for x in 0..100 {
|
||
assert_eq!(img.get_pixel(x, y)[0], normalized.get_pixel(x, y)[0]);
|
||
}
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_normalize_contrast_narrow_range() {
|
||
// Image with narrow range should be stretched
|
||
let mut img = GrayImage::new(100, 100);
|
||
for y in 0..100 {
|
||
for x in 0..100 {
|
||
img.put_pixel(x, y, Luma([100])); // Constant mid-gray
|
||
}
|
||
}
|
||
|
||
let normalized = normalize_contrast(&img);
|
||
// Constant image should be unchanged
|
||
for y in 0..100 {
|
||
for x in 0..100 {
|
||
assert_eq!(normalized.get_pixel(x, y)[0], 100);
|
||
}
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_binarize_otsu() {
|
||
// Create an image with distinct foreground and background
|
||
let mut img = GrayImage::new(100, 100);
|
||
for y in 0..100 {
|
||
for x in 0..100 {
|
||
// Left half dark (text), right half light (background)
|
||
let val = if x < 50 { 50 } else { 200 };
|
||
img.put_pixel(x, y, Luma([val]));
|
||
}
|
||
}
|
||
|
||
let binary = binarize_otsu(&img);
|
||
|
||
// Check that we get a binary output
|
||
for y in 0..100 {
|
||
for x in 0..100 {
|
||
let pixel = binary.get_pixel(x, y)[0];
|
||
assert!(
|
||
pixel == 0 || pixel == 255,
|
||
"Pixel should be 0 or 255, got {}",
|
||
pixel
|
||
);
|
||
}
|
||
}
|
||
|
||
// Left half should be darker (text)
|
||
let left_sum: u32 = (0..50).map(|x| binary.get_pixel(x, 50)[0] as u32).sum();
|
||
let right_sum: u32 = (50..100).map(|x| binary.get_pixel(x, 50)[0] as u32).sum();
|
||
assert!(left_sum < right_sum, "Left half should be darker");
|
||
}
|
||
|
||
#[test]
|
||
fn test_binarize_sauvola() {
|
||
// Create a simple gradient image
|
||
let mut img = GrayImage::new(100, 100);
|
||
for y in 0..100 {
|
||
for x in 0..100 {
|
||
let val = (x + y) as u8 / 2;
|
||
img.put_pixel(x, y, Luma([val]));
|
||
}
|
||
}
|
||
|
||
let binary = binarize_sauvola(&img);
|
||
|
||
// Check that we get a binary output
|
||
for y in 0..100 {
|
||
for x in 0..100 {
|
||
let pixel = binary.get_pixel(x, y)[0];
|
||
assert!(
|
||
pixel == 0 || pixel == 255,
|
||
"Pixel should be 0 or 255, got {}",
|
||
pixel
|
||
);
|
||
}
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_denoise_median() {
|
||
// Create an image with salt-and-pepper noise
|
||
let mut img = GrayImage::from_pixel(100, 100, Luma([128]));
|
||
// Add some noise
|
||
img.put_pixel(50, 50, Luma([0])); // pepper
|
||
img.put_pixel(51, 50, Luma([255])); // salt
|
||
img.put_pixel(50, 51, Luma([255])); // salt
|
||
img.put_pixel(51, 51, Luma([0])); // pepper
|
||
|
||
let denoised = denoise_median(&img);
|
||
|
||
// The noisy pixels should be closer to 128 after median filtering
|
||
let center = denoised.get_pixel(50, 50)[0];
|
||
assert!(
|
||
center > 64 && center < 192,
|
||
"Denoised pixel should be near middle, got {}",
|
||
center
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_physical_scan() {
|
||
let img = create_horizontal_lines_image();
|
||
let (preprocessed, diagnostics) =
|
||
preprocess(&img, ImageSource::PhysicalScan).expect("Preprocess failed");
|
||
|
||
// Should have border padding
|
||
assert_eq!(preprocessed.width(), img.width() + 20);
|
||
assert_eq!(preprocessed.height(), img.height() + 20);
|
||
|
||
// Diagnostics should not have errors
|
||
assert!(!diagnostics
|
||
.iter()
|
||
.any(|d| d.code == DiagCode::ImgUnsupportedFormat));
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_digital_origin() {
|
||
let img = create_horizontal_lines_image();
|
||
let (preprocessed, diagnostics) =
|
||
preprocess(&img, ImageSource::DigitalOrigin).expect("Preprocess failed");
|
||
|
||
// Should have border padding
|
||
assert_eq!(preprocessed.width(), img.width() + 20);
|
||
assert_eq!(preprocessed.height(), img.height() + 20);
|
||
|
||
// Diagnostics should not have errors
|
||
assert!(!diagnostics
|
||
.iter()
|
||
.any(|d| d.code == DiagCode::ImgUnsupportedFormat));
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_jbig2() {
|
||
let img = create_horizontal_lines_image();
|
||
let (preprocessed, diagnostics) =
|
||
preprocess(&img, ImageSource::Jbig2).expect("Preprocess failed");
|
||
|
||
// Should have border padding
|
||
assert_eq!(preprocessed.width(), img.width() + 20);
|
||
assert_eq!(preprocessed.height(), img.height() + 20);
|
||
|
||
// Diagnostics should not have errors
|
||
assert!(!diagnostics
|
||
.iter()
|
||
.any(|d| d.code == DiagCode::ImgUnsupportedFormat));
|
||
}
|
||
|
||
#[test]
|
||
fn test_image_source_is_jbig2() {
|
||
assert!(ImageSource::Jbig2.is_jbig2());
|
||
assert!(!ImageSource::PhysicalScan.is_jbig2());
|
||
assert!(!ImageSource::DigitalOrigin.is_jbig2());
|
||
}
|
||
|
||
#[test]
|
||
fn test_image_source_is_digital() {
|
||
assert!(ImageSource::DigitalOrigin.is_digital());
|
||
assert!(!ImageSource::PhysicalScan.is_digital());
|
||
assert!(!ImageSource::Jbig2.is_digital());
|
||
}
|
||
|
||
#[test]
|
||
fn test_image_source_is_physical_scan() {
|
||
assert!(ImageSource::PhysicalScan.is_physical_scan());
|
||
assert!(!ImageSource::DigitalOrigin.is_physical_scan());
|
||
assert!(!ImageSource::Jbig2.is_physical_scan());
|
||
}
|
||
|
||
// Integration tests with fixtures
|
||
|
||
/// Helper to load a fixture image.
|
||
fn load_fixture(path: &str) -> GrayImage {
|
||
image::io::Reader::with_format(
|
||
std::io::Cursor::new(std::fs::read(path).unwrap()),
|
||
image::ImageFormat::Png,
|
||
)
|
||
.decode()
|
||
.unwrap()
|
||
.to_luma8()
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_skewed_2deg_deskews() {
|
||
// Acceptance criterion: 2-deg skewed fixture deskewed within 0.1 deg
|
||
let source = load_fixture("tests/fixtures/preprocess/skewed_2deg/source.png");
|
||
let (preprocessed, diagnostics) =
|
||
preprocess(&source, ImageSource::PhysicalScan).expect("Preprocess failed");
|
||
|
||
// Should have border padding
|
||
assert_eq!(preprocessed.width(), source.width() + 20);
|
||
assert_eq!(preprocessed.height(), source.height() + 20);
|
||
|
||
// Verify deskewing by checking that a second deskew pass detects near-zero skew
|
||
// (after removing the border padding for the check)
|
||
let cropped = image::imageops::crop_imm(
|
||
&preprocessed,
|
||
BORDER_PADDING,
|
||
BORDER_PADDING,
|
||
preprocessed.width() - 2 * BORDER_PADDING,
|
||
preprocessed.height() - 2 * BORDER_PADDING,
|
||
)
|
||
.to_image();
|
||
|
||
let (_, second_angle, _) = deskew(&cropped).expect("Second deskew failed");
|
||
assert!(
|
||
second_angle.abs() < 0.1,
|
||
"Second pass should detect near-zero skew, got {}",
|
||
second_angle
|
||
);
|
||
|
||
// No errors in diagnostics
|
||
assert!(!diagnostics
|
||
.iter()
|
||
.any(|d| d.code == DiagCode::ImgUnsupportedFormat));
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_uneven_lighting_binarizes() {
|
||
// Acceptance criterion: uneven-lighting binarized correctly
|
||
let source = load_fixture("tests/fixtures/preprocess/uneven_lighting/source.png");
|
||
let (preprocessed, diagnostics) =
|
||
preprocess(&source, ImageSource::PhysicalScan).expect("Preprocess failed");
|
||
|
||
// Should have border padding
|
||
assert_eq!(preprocessed.width(), source.width() + 20);
|
||
assert_eq!(preprocessed.height(), source.height() + 20);
|
||
|
||
// Check that the inner region (excluding padding) is binarized
|
||
for y in BORDER_PADDING..preprocessed.height() - BORDER_PADDING {
|
||
for x in BORDER_PADDING..preprocessed.width() - BORDER_PADDING {
|
||
let pixel = preprocessed.get_pixel(x, y)[0];
|
||
assert!(
|
||
pixel == 0 || pixel == 255,
|
||
"Pixel should be binary (0 or 255), got {}",
|
||
pixel
|
||
);
|
||
}
|
||
}
|
||
|
||
// No errors in diagnostics
|
||
assert!(!diagnostics
|
||
.iter()
|
||
.any(|d| d.code == DiagCode::ImgUnsupportedFormat));
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_clean_digital_binarizes() {
|
||
// Acceptance criterion: clean digital origin binarized with Otsu
|
||
let source = load_fixture("tests/fixtures/preprocess/clean_digital/source.png");
|
||
let (preprocessed, diagnostics) =
|
||
preprocess(&source, ImageSource::DigitalOrigin).expect("Preprocess failed");
|
||
|
||
// Should have border padding
|
||
assert_eq!(preprocessed.width(), source.width() + 20);
|
||
assert_eq!(preprocessed.height(), source.height() + 20);
|
||
|
||
// Check that the inner region is binarized
|
||
for y in BORDER_PADDING..preprocessed.height() - BORDER_PADDING {
|
||
for x in BORDER_PADDING..preprocessed.width() - BORDER_PADDING {
|
||
let pixel = preprocessed.get_pixel(x, y)[0];
|
||
assert!(
|
||
pixel == 0 || pixel == 255,
|
||
"Pixel should be binary (0 or 255), got {}",
|
||
pixel
|
||
);
|
||
}
|
||
}
|
||
|
||
// No errors in diagnostics
|
||
assert!(!diagnostics
|
||
.iter()
|
||
.any(|d| d.code == DiagCode::ImgUnsupportedFormat));
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_jbig2_only_pads() {
|
||
// Acceptance criterion: JBIG2 untouched except for border padding
|
||
let source = load_fixture("tests/fixtures/preprocess/jbig2_scan/source.png");
|
||
let (preprocessed, diagnostics) =
|
||
preprocess(&source, ImageSource::Jbig2).expect("Preprocess failed");
|
||
|
||
// Should have border padding
|
||
assert_eq!(preprocessed.width(), source.width() + 20);
|
||
assert_eq!(preprocessed.height(), source.height() + 20);
|
||
|
||
// The inner region should match the original exactly (no binarization/denoise)
|
||
for y in 0..source.height() {
|
||
for x in 0..source.width() {
|
||
let orig = source.get_pixel(x, y)[0];
|
||
let pad = preprocessed.get_pixel(x + BORDER_PADDING, y + BORDER_PADDING)[0];
|
||
assert_eq!(
|
||
orig, pad,
|
||
"JBIG2 inner pixel at ({}, {}) should match original",
|
||
x, y
|
||
);
|
||
}
|
||
}
|
||
|
||
// No errors in diagnostics
|
||
assert!(!diagnostics
|
||
.iter()
|
||
.any(|d| d.code == DiagCode::ImgUnsupportedFormat));
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_deterministic() {
|
||
// Acceptance criterion: same input -> bit-identical output
|
||
let source = load_fixture("tests/fixtures/preprocess/clean_digital/source.png");
|
||
|
||
let (result1, _) =
|
||
preprocess(&source, ImageSource::DigitalOrigin).expect("First preprocess failed");
|
||
let (result2, _) =
|
||
preprocess(&source, ImageSource::DigitalOrigin).expect("Second preprocess failed");
|
||
|
||
// Compare pixel-by-pixel
|
||
assert_eq!(result1.dimensions(), result2.dimensions());
|
||
for y in 0..result1.height() {
|
||
for x in 0..result1.width() {
|
||
let p1 = result1.get_pixel(x, y)[0];
|
||
let p2 = result2.get_pixel(x, y)[0];
|
||
assert_eq!(p1, p2, "Pixels differ at ({}, {}): {} vs {}", x, y, p1, p2);
|
||
}
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_preprocess_border_padding_pixel_perfect() {
|
||
// Acceptance criterion: padding adds exactly 10px on each side
|
||
let source = load_fixture("tests/fixtures/preprocess/clean_digital/source.png");
|
||
let (preprocessed, _) =
|
||
preprocess(&source, ImageSource::DigitalOrigin).expect("Preprocess failed");
|
||
|
||
// Check top border is white
|
||
for x in 0..preprocessed.width() {
|
||
for y in 0..BORDER_PADDING {
|
||
assert_eq!(
|
||
preprocessed.get_pixel(x, y)[0],
|
||
255,
|
||
"Top border should be white"
|
||
);
|
||
}
|
||
}
|
||
|
||
// Check bottom border is white
|
||
for x in 0..preprocessed.width() {
|
||
for y in preprocessed.height() - BORDER_PADDING..preprocessed.height() {
|
||
assert_eq!(
|
||
preprocessed.get_pixel(x, y)[0],
|
||
255,
|
||
"Bottom border should be white"
|
||
);
|
||
}
|
||
}
|
||
|
||
// Check left border is white
|
||
for y in 0..preprocessed.height() {
|
||
for x in 0..BORDER_PADDING {
|
||
assert_eq!(
|
||
preprocessed.get_pixel(x, y)[0],
|
||
255,
|
||
"Left border should be white"
|
||
);
|
||
}
|
||
}
|
||
|
||
// Check right border is white
|
||
for y in 0..preprocessed.height() {
|
||
for x in preprocessed.width() - BORDER_PADDING..preprocessed.width() {
|
||
assert_eq!(
|
||
preprocessed.get_pixel(x, y)[0],
|
||
255,
|
||
"Right border should be white"
|
||
);
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
// Benchmarks for preprocessing performance
|
||
|
||
#[cfg(all(test, feature = "ocr", target_arch = "x86_64"))]
|
||
mod benches {
|
||
use super::*;
|
||
use std::time::{Duration, Instant};
|
||
|
||
/// A4 page size at 300 DPI: 2480 x 3508 pixels.
|
||
/// This is a typical input size for preprocessing.
|
||
const A4_WIDTH: u32 = 2480;
|
||
const A4_HEIGHT: u32 = 3508;
|
||
|
||
/// Create an A4-sized test image with a simple pattern.
|
||
fn create_a4_test_image() -> GrayImage {
|
||
let mut img = GrayImage::new(A4_WIDTH, A4_HEIGHT);
|
||
|
||
// Fill with a gradient pattern (simulating a scanned document)
|
||
for y in 0..A4_HEIGHT {
|
||
for x in 0..A4_WIDTH {
|
||
// Create horizontal bands (simulating text lines)
|
||
let line_y = (y / 20) * 20 + 10;
|
||
let in_text_line = (y as i32 - line_y as i32).abs() < 6;
|
||
let in_text = x % 60 < 50;
|
||
|
||
let val = if in_text_line && in_text { 0 } else { 220 };
|
||
img.put_pixel(x, y, Luma([val]));
|
||
}
|
||
}
|
||
|
||
img
|
||
}
|
||
|
||
#[test]
|
||
fn benchmark_preprocess_a4_physical_scan() {
|
||
// Acceptance criterion: A4-page benchmark < 500 ms on CI
|
||
let img = create_a4_test_image();
|
||
|
||
let start = Instant::now();
|
||
let (result, diagnostics) =
|
||
preprocess(&img, ImageSource::PhysicalScan).expect("Preprocess failed");
|
||
let elapsed = start.elapsed();
|
||
|
||
println!("A4 (2480x3508) PhysicalScan preprocess time: {:?}", elapsed);
|
||
|
||
// Verify correctness
|
||
assert_eq!(result.width(), A4_WIDTH + 20);
|
||
assert_eq!(result.height(), A4_HEIGHT + 20);
|
||
|
||
// Check performance requirement
|
||
assert!(
|
||
elapsed < Duration::from_millis(500),
|
||
"A4 preprocess took {:?}, expected < 500ms",
|
||
elapsed
|
||
);
|
||
|
||
println!("✓ A4 preprocessing completed within 500ms limit");
|
||
}
|
||
|
||
#[test]
|
||
fn benchmark_preprocess_a4_digital_origin() {
|
||
let img = create_a4_test_image();
|
||
|
||
let start = Instant::now();
|
||
let (result, _) = preprocess(&img, ImageSource::DigitalOrigin).expect("Preprocess failed");
|
||
let elapsed = start.elapsed();
|
||
|
||
println!(
|
||
"A4 (2480x3508) DigitalOrigin preprocess time: {:?}",
|
||
elapsed
|
||
);
|
||
|
||
assert_eq!(result.width(), A4_WIDTH + 20);
|
||
assert_eq!(result.height(), A4_HEIGHT + 20);
|
||
|
||
assert!(
|
||
elapsed < Duration::from_millis(500),
|
||
"A4 preprocess took {:?}, expected < 500ms",
|
||
elapsed
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn benchmark_preprocess_a4_jbig2() {
|
||
let img = create_a4_test_image();
|
||
|
||
let start = Instant::now();
|
||
let (result, _) = preprocess(&img, ImageSource::Jbig2).expect("Preprocess failed");
|
||
let elapsed = start.elapsed();
|
||
|
||
println!("A4 (2480x3508) Jbig2 preprocess time: {:?}", elapsed);
|
||
|
||
assert_eq!(result.width(), A4_WIDTH + 20);
|
||
assert_eq!(result.height(), A4_HEIGHT + 20);
|
||
|
||
// JBIG2 should be faster (skips many steps)
|
||
assert!(
|
||
elapsed < Duration::from_millis(200),
|
||
"A4 JBIG2 preprocess took {:?}, expected < 200ms",
|
||
elapsed
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn benchmark_individual_steps() {
|
||
let img = create_a4_test_image();
|
||
|
||
// Benchmark deskew
|
||
let start = Instant::now();
|
||
let (deskewed, angle, _) = deskew(&img).expect("Deskew failed");
|
||
let deskew_time = start.elapsed();
|
||
println!("Deskew time: {:?} (angle: {}°)", deskew_time, angle);
|
||
|
||
// Benchmark contrast normalization
|
||
let start = Instant::now();
|
||
let normalized = normalize_contrast(&deskewed);
|
||
let contrast_time = start.elapsed();
|
||
println!("Contrast normalization time: {:?}", contrast_time);
|
||
|
||
// Benchmark Sauvola binarization
|
||
let start = Instant::now();
|
||
let binary = binarize_sauvola(&normalized);
|
||
let sauvola_time = start.elapsed();
|
||
println!("Sauvola binarization time: {:?}", sauvola_time);
|
||
|
||
// Benchmark denoising
|
||
let start = Instant::now();
|
||
let denoised = denoise_median(&binary);
|
||
let denoise_time = start.elapsed();
|
||
println!("Median denoise time: {:?}", denoise_time);
|
||
|
||
// Benchmark padding
|
||
let start = Instant::now();
|
||
let padded = add_border_padding(&denoised);
|
||
let pad_time = start.elapsed();
|
||
println!("Border padding time: {:?}", pad_time);
|
||
|
||
let total = deskew_time + contrast_time + sauvola_time + denoise_time + pad_time;
|
||
println!("Total individual step time: {:?}", total);
|
||
|
||
// Verify final result
|
||
assert_eq!(padded.width(), A4_WIDTH + 20);
|
||
assert_eq!(padded.height(), A4_HEIGHT + 20);
|
||
|
||
assert!(
|
||
total < Duration::from_millis(500),
|
||
"Total step time took {:?}, expected < 500ms",
|
||
total
|
||
);
|
||
}
|
||
}
|