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336 lines
13 KiB
Rust
336 lines
13 KiB
Rust
/*
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* Copyright 2009 ZXing authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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// package com.google.zxing.common;
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// import com.google.zxing.Binarizer;
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// import com.google.zxing.LuminanceSource;
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// import com.google.zxing.NotFoundException;
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use std::borrow::Cow;
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use once_cell::unsync::OnceCell;
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use crate::common::Result;
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use crate::{Binarizer, LuminanceSource};
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use super::{BitArray, BitMatrix, GlobalHistogramBinarizer};
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/**
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* This class implements a local thresholding algorithm, which while slower than the
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* GlobalHistogramBinarizer, is fairly efficient for what it does. It is designed for
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* high frequency images of barcodes with black data on white backgrounds. For this application,
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* it does a much better job than a global blackpoint with severe shadows and gradients.
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* However it tends to produce artifacts on lower frequency images and is therefore not
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* a good general purpose binarizer for uses outside ZXing.
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*
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* This class extends GlobalHistogramBinarizer, using the older histogram approach for 1D readers,
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* and the newer local approach for 2D readers. 1D decoding using a per-row histogram is already
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* inherently local, and only fails for horizontal gradients. We can revisit that problem later,
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* but for now it was not a win to use local blocks for 1D.
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*
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* This Binarizer is the default for the unit tests and the recommended class for library users.
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*
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* @author dswitkin@google.com (Daniel Switkin)
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*/
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pub struct HybridBinarizer<LS: LuminanceSource> {
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//width: usize,
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//height: usize,
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//source: Box<dyn LuminanceSource>,
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ghb: GlobalHistogramBinarizer<LS>,
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black_matrix: OnceCell<BitMatrix>,
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}
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impl<LS: LuminanceSource> Binarizer for HybridBinarizer<LS> {
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type Source = LS;
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fn get_luminance_source(&self) -> &LS {
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self.ghb.get_luminance_source()
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}
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fn get_black_row(&self, y: usize) -> Result<Cow<BitArray>> {
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self.ghb.get_black_row(y)
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}
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/**
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* Calculates the final BitMatrix once for all requests. This could be called once from the
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* constructor instead, but there are some advantages to doing it lazily, such as making
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* profiling easier, and not doing heavy lifting when callers don't expect it.
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*/
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fn get_black_matrix(&self) -> Result<&BitMatrix> {
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let matrix = self
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.black_matrix
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.get_or_try_init(|| Self::calculateBlackMatrix(&self.ghb))?;
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Ok(matrix)
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}
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fn create_binarizer(&self, source: LS) -> Self {
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Self::new(source)
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}
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fn get_width(&self) -> usize {
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self.ghb.get_width()
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}
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fn get_height(&self) -> usize {
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self.ghb.get_height()
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}
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}
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// This class uses 5x5 blocks to compute local luminance, where each block is 8x8 pixels.
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// So this is the smallest dimension in each axis we can accept.
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const BLOCK_SIZE_POWER: usize = 3;
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const BLOCK_SIZE: usize = 1 << BLOCK_SIZE_POWER; // ...0100...00
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const BLOCK_SIZE_MASK: usize = BLOCK_SIZE - 1; // ...0011...11
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const MINIMUM_DIMENSION: usize = BLOCK_SIZE * 5;
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const MIN_DYNAMIC_RANGE: usize = 24;
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impl<LS: LuminanceSource> HybridBinarizer<LS> {
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pub fn new(source: LS) -> Self {
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let ghb = GlobalHistogramBinarizer::new(source);
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Self {
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black_matrix: OnceCell::new(),
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ghb,
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}
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}
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fn calculateBlackMatrix<LS2: LuminanceSource>(
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ghb: &GlobalHistogramBinarizer<LS2>,
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) -> Result<BitMatrix> {
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// let matrix;
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let source = ghb.get_luminance_source();
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let width = source.get_width();
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let height = source.get_height();
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// dbg!(matrix.to_string());
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if width >= MINIMUM_DIMENSION && height >= MINIMUM_DIMENSION {
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let luminances = source.get_matrix();
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let mut sub_width = width >> BLOCK_SIZE_POWER;
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if (width & BLOCK_SIZE_MASK) != 0 {
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sub_width += 1;
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}
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let mut sub_height = height >> BLOCK_SIZE_POWER;
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if (height & BLOCK_SIZE_MASK) != 0 {
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sub_height += 1;
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}
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let black_points = Self::calculateBlackPoints(
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&luminances,
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sub_width as u32,
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sub_height as u32,
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width as u32,
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height as u32,
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);
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let mut new_matrix = BitMatrix::new(width as u32, height as u32)?;
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Self::calculateThresholdForBlock(
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&luminances,
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sub_width as u32,
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sub_height as u32,
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width as u32,
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height as u32,
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&black_points,
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&mut new_matrix,
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);
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Ok(new_matrix)
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} else {
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// If the image is too small, fall back to the global histogram approach.
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let m = ghb.get_black_matrix()?;
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Ok(m.clone())
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}
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}
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/**
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* For each block in the image, calculate the average black point using a 5x5 grid
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* of the blocks around it. Also handles the corner cases (fractional blocks are computed based
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* on the last pixels in the row/column which are also used in the previous block).
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*/
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fn calculateThresholdForBlock(
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luminances: &[u8],
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sub_width: u32,
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sub_height: u32,
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width: u32,
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height: u32,
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black_points: &[Vec<u32>],
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matrix: &mut BitMatrix,
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) {
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let maxYOffset = height - BLOCK_SIZE as u32;
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let maxXOffset = width - BLOCK_SIZE as u32;
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for y in 0..sub_height {
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// for (int y = 0; y < subHeight; y++) {
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let mut yoffset = y << BLOCK_SIZE_POWER;
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if yoffset > maxYOffset {
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yoffset = maxYOffset;
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}
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let top = Self::cap(y, sub_height - 3);
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for x in 0..sub_width {
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// for (int x = 0; x < subWidth; x++) {
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let mut xoffset = x << BLOCK_SIZE_POWER;
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if xoffset > maxXOffset {
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xoffset = maxXOffset;
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}
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let left = Self::cap(x, sub_width - 3);
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let mut sum = 0;
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for z in -2..=2 {
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// for (int z = -2; z <= 2; z++) {
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let blackRow = &black_points[(top as i32 + z) as usize];
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sum += blackRow[(left - 2) as usize]
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+ blackRow[(left - 1) as usize]
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+ blackRow[left as usize]
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+ blackRow[(left + 1) as usize]
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+ blackRow[(left + 2) as usize];
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}
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let average = sum / 25;
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Self::thresholdBlock(luminances, xoffset, yoffset, average, width, matrix);
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}
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}
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}
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#[inline(always)]
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fn cap(value: u32, max: u32) -> u32 {
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if value < 2 {
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2
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} else {
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value.min(max)
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}
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}
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/**
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* Applies a single threshold to a block of pixels.
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*/
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fn thresholdBlock(
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luminances: &[u8],
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xoffset: u32,
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yoffset: u32,
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threshold: u32,
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stride: u32,
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matrix: &mut BitMatrix,
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) {
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let mut offset = yoffset * stride + xoffset;
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for y in 0..BLOCK_SIZE {
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// for (int y = 0, offset = yoffset * stride + xoffset; y < HybridBinarizer::BLOCK_SIZE; y++, offset += stride) {
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for x in 0..BLOCK_SIZE {
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// for (int x = 0; x < HybridBinarizer::BLOCK_SIZE; x++) {
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// Comparison needs to be <= so that black == 0 pixels are black even if the threshold is 0.
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if luminances[offset as usize + x] as u32 <= threshold {
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matrix.set(xoffset + x as u32, yoffset + y as u32);
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}
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}
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offset += stride;
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}
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}
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/**
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* Calculates a single black point for each block of pixels and saves it away.
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* See the following thread for a discussion of this algorithm:
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* http://groups.google.com/group/zxing/browse_thread/thread/d06efa2c35a7ddc0
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*/
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fn calculateBlackPoints(
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luminances: &[u8],
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subWidth: u32,
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subHeight: u32,
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width: u32,
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height: u32,
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) -> Vec<Vec<u32>> {
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let maxYOffset = height as usize - BLOCK_SIZE;
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let maxXOffset = width as usize - BLOCK_SIZE;
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let mut blackPoints = vec![vec![0; subWidth as usize]; subHeight as usize];
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for y in 0..subHeight {
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// for (int y = 0; y < subHeight; y++) {
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let mut yoffset = y << BLOCK_SIZE_POWER;
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if yoffset > maxYOffset as u32 {
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yoffset = maxYOffset as u32;
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}
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for x in 0..subWidth {
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// for (int x = 0; x < subWidth; x++) {
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let mut xoffset = x << BLOCK_SIZE_POWER;
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if xoffset > maxXOffset as u32 {
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xoffset = maxXOffset as u32;
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}
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let mut sum: u32 = 0;
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let mut min = 0xff;
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let mut max = 0;
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let mut offset = yoffset * width + xoffset;
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let mut yy = 0;
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while yy < BLOCK_SIZE {
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// for (int yy = 0, offset = yoffset * width + xoffset; yy < HybridBinarizer::BLOCK_SIZE; yy++, offset += width) {
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for xx in 0..BLOCK_SIZE {
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// for (int xx = 0; xx < HybridBinarizer::BLOCK_SIZE; xx++) {
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let pixel = luminances[offset as usize + xx];
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sum += pixel as u32;
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// still looking for good contrast
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if pixel < min {
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min = pixel;
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}
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if pixel > max {
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max = pixel;
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}
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}
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// short-circuit min/max tests once dynamic range is met
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if (max - min) as usize > MIN_DYNAMIC_RANGE {
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// finish the rest of the rows quickly
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offset += width;
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yy += 1;
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while yy < BLOCK_SIZE {
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// for (yy++, offset += width; yy < HybridBinarizer::BLOCK_SIZE; yy++, offset += width) {
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for xx in 0..BLOCK_SIZE {
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// for (int xx = 0; xx < BLOCK_SIZE; xx++) {
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sum += luminances[offset as usize + xx] as u32;
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}
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yy += 1;
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offset += width;
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}
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break;
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}
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yy += 1;
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offset += width;
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}
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// The default estimate is the average of the values in the block.
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let mut average = sum >> (BLOCK_SIZE_POWER * 2);
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if (max - min) as usize <= MIN_DYNAMIC_RANGE {
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// If variation within the block is low, assume this is a block with only light or only
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// dark pixels. In that case we do not want to use the average, as it would divide this
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// low contrast area into black and white pixels, essentially creating data out of noise.
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//
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// The default assumption is that the block is light/background. Since no estimate for
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// the level of dark pixels exists locally, use half the min for the block.
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average = min as u32 / 2;
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if y > 0 && x > 0 {
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// Correct the "white background" assumption for blocks that have neighbors by comparing
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// the pixels in this block to the previously calculated black points. This is based on
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// the fact that dark barcode symbology is always surrounded by some amount of light
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// background for which reasonable black point estimates were made. The bp estimated at
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// the boundaries is used for the interior.
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// The (min < bp) is arbitrary but works better than other heuristics that were tried.
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let average_neighbor_black_point: u32 = (blackPoints[y as usize - 1]
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[x as usize]
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+ (2 * blackPoints[y as usize][x as usize - 1])
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+ blackPoints[y as usize - 1][x as usize - 1])
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/ 4;
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if (min as u32) < average_neighbor_black_point {
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average = average_neighbor_black_point;
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}
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}
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}
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blackPoints[y as usize][x as usize] = average;
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}
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}
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blackPoints
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}
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}
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