src/core/common/GlobalHistogramBinarizer.ts
/*
* Copyright 2009 ZXing authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*namespace com.google.zxing.common {*/
import Binarizer from '../Binarizer';
import LuminanceSource from '../LuminanceSource';
import BitArray from './BitArray';
import BitMatrix from './BitMatrix';
import NotFoundException from '../NotFoundException';
/**
* This Binarizer implementation uses the old ZXing global histogram approach. It is suitable
* for low-end mobile devices which don't have enough CPU or memory to use a local thresholding
* algorithm. However, because it picks a global black point, it cannot handle difficult shadows
* and gradients.
*
* Faster mobile devices and all desktop applications should probably use HybridBinarizer instead.
*
* @author dswitkin@google.com (Daniel Switkin)
* @author Sean Owen
*/
export default class GlobalHistogramBinarizer extends Binarizer {
private static LUMINANCE_BITS = 5;
private static LUMINANCE_SHIFT = 8 - GlobalHistogramBinarizer.LUMINANCE_BITS;
private static LUMINANCE_BUCKETS = 1 << GlobalHistogramBinarizer.LUMINANCE_BITS;
private static EMPTY = Uint8ClampedArray.from([0]);
private luminances: Uint8ClampedArray;
private buckets: Int32Array;
public constructor(source: LuminanceSource) {
super(source);
this.luminances = GlobalHistogramBinarizer.EMPTY;
this.buckets = new Int32Array(GlobalHistogramBinarizer.LUMINANCE_BUCKETS);
}
// Applies simple sharpening to the row data to improve performance of the 1D Readers.
/*@Override*/
public getBlackRow(y: number /*int*/, row: BitArray): BitArray /*throws NotFoundException*/ {
const source = this.getLuminanceSource();
const width = source.getWidth();
if (row === undefined || row === null || row.getSize() < width) {
row = new BitArray(width);
} else {
row.clear();
}
this.initArrays(width);
const localLuminances = source.getRow(y, this.luminances);
const localBuckets = this.buckets;
for (let x = 0; x < width; x++) {
localBuckets[(localLuminances[x] & 0xff) >> GlobalHistogramBinarizer.LUMINANCE_SHIFT]++;
}
const blackPoint = GlobalHistogramBinarizer.estimateBlackPoint(localBuckets);
if (width < 3) {
// Special case for very small images
for (let x = 0; x < width; x++) {
if ((localLuminances[x] & 0xff) < blackPoint) {
row.set(x);
}
}
} else {
let left = localLuminances[0] & 0xff;
let center = localLuminances[1] & 0xff;
for (let x = 1; x < width - 1; x++) {
const right = localLuminances[x + 1] & 0xff;
// A simple -1 4 -1 box filter with a weight of 2.
if (((center * 4) - left - right) / 2 < blackPoint) {
row.set(x);
}
left = center;
center = right;
}
}
return row;
}
// Does not sharpen the data, as this call is intended to only be used by 2D Readers.
/*@Override*/
public getBlackMatrix(): BitMatrix /*throws NotFoundException*/ {
const source = this.getLuminanceSource();
const width = source.getWidth();
const height = source.getHeight();
const matrix = new BitMatrix(width, height);
// Quickly calculates the histogram by sampling four rows from the image. This proved to be
// more robust on the blackbox tests than sampling a diagonal as we used to do.
this.initArrays(width);
const localBuckets = this.buckets;
for (let y = 1; y < 5; y++) {
const row = Math.floor((height * y) / 5);
const localLuminances = source.getRow(row, this.luminances);
const right = Math.floor((width * 4) / 5);
for (let x = Math.floor(width / 5); x < right; x++) {
const pixel = localLuminances[x] & 0xff;
localBuckets[pixel >> GlobalHistogramBinarizer.LUMINANCE_SHIFT]++;
}
}
const blackPoint = GlobalHistogramBinarizer.estimateBlackPoint(localBuckets);
// We delay reading the entire image luminance until the black point estimation succeeds.
// Although we end up reading four rows twice, it is consistent with our motto of
// "fail quickly" which is necessary for continuous scanning.
const localLuminances = source.getMatrix();
for (let y = 0; y < height; y++) {
const offset = y * width;
for (let x = 0; x < width; x++) {
const pixel = localLuminances[offset + x] & 0xff;
if (pixel < blackPoint) {
matrix.set(x, y);
}
}
}
return matrix;
}
/*@Override*/
public createBinarizer(source: LuminanceSource): Binarizer {
return new GlobalHistogramBinarizer(source);
}
private initArrays(luminanceSize: number /*int*/): void {
if (this.luminances.length < luminanceSize) {
this.luminances = new Uint8ClampedArray(luminanceSize);
}
const buckets = this.buckets;
for (let x = 0; x < GlobalHistogramBinarizer.LUMINANCE_BUCKETS; x++) {
buckets[x] = 0;
}
}
private static estimateBlackPoint(buckets: Int32Array): number /*int*/ /*throws NotFoundException*/ {
// Find the tallest peak in the histogram.
const numBuckets = buckets.length;
let maxBucketCount = 0;
let firstPeak = 0;
let firstPeakSize = 0;
for (let x = 0; x < numBuckets; x++) {
if (buckets[x] > firstPeakSize) {
firstPeak = x;
firstPeakSize = buckets[x];
}
if (buckets[x] > maxBucketCount) {
maxBucketCount = buckets[x];
}
}
// Find the second-tallest peak which is somewhat far from the tallest peak.
let secondPeak = 0;
let secondPeakScore = 0;
for (let x = 0; x < numBuckets; x++) {
const distanceToBiggest = x - firstPeak;
// Encourage more distant second peaks by multiplying by square of distance.
const score = buckets[x] * distanceToBiggest * distanceToBiggest;
if (score > secondPeakScore) {
secondPeak = x;
secondPeakScore = score;
}
}
// Make sure firstPeak corresponds to the black peak.
if (firstPeak > secondPeak) {
const temp = firstPeak;
firstPeak = secondPeak;
secondPeak = temp;
}
// If there is too little contrast in the image to pick a meaningful black point, throw rather
// than waste time trying to decode the image, and risk false positives.
if (secondPeak - firstPeak <= numBuckets / 16) {
throw new NotFoundException();
}
// Find a valley between them that is low and closer to the white peak.
let bestValley = secondPeak - 1;
let bestValleyScore = -1;
for (let x = secondPeak - 1; x > firstPeak; x--) {
const fromFirst = x - firstPeak;
const score = fromFirst * fromFirst * (secondPeak - x) * (maxBucketCount - buckets[x]);
if (score > bestValleyScore) {
bestValley = x;
bestValleyScore = score;
}
}
return bestValley << GlobalHistogramBinarizer.LUMINANCE_SHIFT;
}
}