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302 lines
14 KiB
Rust
302 lines
14 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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/**
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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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// 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: i32 = 3;
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// ...0100...00
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const BLOCK_SIZE: i32 = 1 << BLOCK_SIZE_POWER;
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// ...0011...11
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const BLOCK_SIZE_MASK: i32 = BLOCK_SIZE - 1;
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const MINIMUM_DIMENSION: i32 = BLOCK_SIZE * 5;
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const MIN_DYNAMIC_RANGE: i32 = 24;
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pub struct HybridBinarizer {
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super: GlobalHistogramBinarizer;
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let mut matrix: BitMatrix;
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}
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impl HybridBinarizer {
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pub fn new( source: &LuminanceSource) -> HybridBinarizer {
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super(source);
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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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pub fn get_black_matrix(&self) -> /* throws NotFoundException */Result<BitMatrix, Rc<Exception>> {
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if self.matrix != null {
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return Ok(self.matrix);
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}
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let source: LuminanceSource = get_luminance_source();
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let width: i32 = source.get_width();
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let height: i32 = source.get_height();
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if width >= MINIMUM_DIMENSION && height >= MINIMUM_DIMENSION {
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let luminances: Vec<i8> = source.get_matrix();
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let sub_width: i32 = 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 sub_height: i32 = 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: Vec<Vec<i32>> = ::calculate_black_points(&luminances, sub_width, sub_height, width, height);
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let new_matrix: BitMatrix = BitMatrix::new(width, height);
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::calculate_threshold_for_block(&luminances, sub_width, sub_height, width, height, &black_points, new_matrix);
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self.matrix = 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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self.matrix = super.get_black_matrix();
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}
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return Ok(self.matrix);
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}
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pub fn create_binarizer(&self, source: &LuminanceSource) -> Binarizer {
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return HybridBinarizer::new(source);
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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 calculate_threshold_for_block( luminances: &Vec<i8>, sub_width: i32, sub_height: i32, width: i32, height: i32, black_points: &Vec<Vec<i32>>, matrix: &BitMatrix) {
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let max_y_offset: i32 = height - BLOCK_SIZE;
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let max_x_offset: i32 = width - BLOCK_SIZE;
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{
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let mut y: i32 = 0;
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while y < sub_height {
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{
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let mut yoffset: i32 = y << BLOCK_SIZE_POWER;
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if yoffset > max_y_offset {
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yoffset = max_y_offset;
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}
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let top: i32 = ::cap(y, sub_height - 3);
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{
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let mut x: i32 = 0;
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while x < sub_width {
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{
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let mut xoffset: i32 = x << BLOCK_SIZE_POWER;
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if xoffset > max_x_offset {
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xoffset = max_x_offset;
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}
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let left: i32 = ::cap(x, sub_width - 3);
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let mut sum: i32 = 0;
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{
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let mut z: i32 = -2;
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while z <= 2 {
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{
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let black_row: Vec<i32> = black_points[top + z];
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sum += black_row[left - 2] + black_row[left - 1] + black_row[left] + black_row[left + 1] + black_row[left + 2];
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}
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z += 1;
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}
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}
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let average: i32 = sum / 25;
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::threshold_block(&luminances, xoffset, yoffset, average, width, matrix);
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}
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x += 1;
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}
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}
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}
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y += 1;
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}
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}
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}
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fn cap( value: i32, max: i32) -> i32 {
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return if value < 2 { 2 } else { Math::min(value, max) };
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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 threshold_block( luminances: &Vec<i8>, xoffset: i32, yoffset: i32, threshold: i32, stride: i32, matrix: &BitMatrix) {
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{
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let mut y: i32 = 0, let mut offset: i32 = yoffset * stride + xoffset;
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while y < BLOCK_SIZE {
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{
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{
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let mut x: i32 = 0;
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while x < BLOCK_SIZE {
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{
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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 + x] & 0xFF) <= threshold {
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matrix.set(xoffset + x, yoffset + y);
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}
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}
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x += 1;
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}
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}
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}
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y += 1;
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offset += stride;
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}
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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 calculate_black_points( luminances: &Vec<i8>, sub_width: i32, sub_height: i32, width: i32, height: i32) -> Vec<Vec<i32>> {
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let max_y_offset: i32 = height - BLOCK_SIZE;
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let max_x_offset: i32 = width - BLOCK_SIZE;
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let black_points: [[i32; sub_width]; sub_height] = [[0; sub_width]; sub_height];
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{
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let mut y: i32 = 0;
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while y < sub_height {
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{
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let mut yoffset: i32 = y << BLOCK_SIZE_POWER;
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if yoffset > max_y_offset {
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yoffset = max_y_offset;
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}
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{
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let mut x: i32 = 0;
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while x < sub_width {
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{
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let mut xoffset: i32 = x << BLOCK_SIZE_POWER;
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if xoffset > max_x_offset {
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xoffset = max_x_offset;
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}
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let mut sum: i32 = 0;
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let mut min: i32 = 0xFF;
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let mut max: i32 = 0;
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{
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let mut yy: i32 = 0, let mut offset: i32 = yoffset * width + xoffset;
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while yy < BLOCK_SIZE {
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{
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{
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let mut xx: i32 = 0;
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while xx < BLOCK_SIZE {
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{
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let pixel: i32 = luminances[offset + xx] & 0xFF;
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sum += pixel;
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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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xx += 1;
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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 > MIN_DYNAMIC_RANGE {
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// finish the rest of the rows quickly
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{
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yy += 1;
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offset += width;
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while yy < BLOCK_SIZE {
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{
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{
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let mut xx: i32 = 0;
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while xx < BLOCK_SIZE {
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{
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sum += luminances[offset + xx] & 0xFF;
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}
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xx += 1;
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}
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}
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}
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yy += 1;
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offset += width;
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}
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}
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}
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}
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yy += 1;
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offset += width;
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}
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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: i32 = sum >> (BLOCK_SIZE_POWER * 2);
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if max - min <= 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 / 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: i32 = (black_points[y - 1][x] + (2 * black_points[y][x - 1]) + black_points[y - 1][x - 1]) / 4;
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if min < 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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black_points[y][x] = average;
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}
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x += 1;
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}
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}
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}
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y += 1;
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}
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}
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return black_points;
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}
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}
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