2021-08-05 00:02:35 +02:00

729 lines
25 KiB
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Executable File

#import "ocr.h"
#include <vector>
#include <utility>
#include <string>
#include <math.h>
#include <stdint.h>
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include "fast-edge.h"
#include "genann.h"
#import "LegacyComponentsInternal.h"
#ifndef max
#define max(a, b) (a>b ? a : b)
#define min(a, b) (a<b ? a : b)
#endif
namespace ocr{
struct line{
double theta;
double r;
};
std::vector<line> detectLines(struct image* img, int threshold){
// The size of the neighbourhood in which to search for other local maxima
const int neighbourhoodSize = 4;
// How many discrete values of theta shall we check?
const int maxTheta = 180;
// Using maxTheta, work out the step
const double thetaStep = M_PI / maxTheta;
int width=img->width;
int height=img->height;
// Calculate the maximum height the hough array needs to have
int houghHeight = (int) (sqrt(2.0) * max(height, width)) / 2;
// Double the height of the hough array to cope with negative r values
int doubleHeight = 2 * houghHeight;
// Create the hough array
int* houghArray = new int[maxTheta*doubleHeight];
memset(houghArray, 0, sizeof(int)*maxTheta*doubleHeight);
// Find edge points and vote in array
int centerX = width / 2;
int centerY = height / 2;
// Count how many points there are
int numPoints = 0;
// cache the values of sin and cos for faster processing
double* sinCache = new double[maxTheta];
double* cosCache = new double[maxTheta];
for (int t = 0; t < maxTheta; t++) {
double realTheta = t * thetaStep;
sinCache[t] = sin(realTheta);
cosCache[t] = cos(realTheta);
}
// Now find edge points and update the hough array
for (int x = 0; x < width; x++) {
for (int y = 0; y < height; y++) {
// Find non-black pixels
if ((img->pixel_data[y*width+x] & 0x000000ff) != 0) {
// Go through each value of theta
for (int t = 0; t < maxTheta; t++) {
//Work out the r values for each theta step
int r = (int) (((x - centerX) * cosCache[t]) + ((y - centerY) * sinCache[t]));
// this copes with negative values of r
r += houghHeight;
if (r < 0 || r >= doubleHeight) continue;
// Increment the hough array
houghArray[t*doubleHeight+r]++;
}
numPoints++;
}
}
}
// Initialise the vector of lines that we'll return
std::vector<line> lines;
// Only proceed if the hough array is not empty
if (numPoints == 0){
delete[] houghArray;
delete[] sinCache;
delete[] cosCache;
return lines;
}
// Search for local peaks above threshold to draw
for (int t = 0; t < maxTheta; t++) {
//loop:
for (int r = neighbourhoodSize; r < doubleHeight - neighbourhoodSize; r++) {
// Only consider points above threshold
if (houghArray[t*doubleHeight+r] > threshold) {
int peak = houghArray[t*doubleHeight+r];
// Check that this peak is indeed the local maxima
for (int dx = -neighbourhoodSize; dx <= neighbourhoodSize; dx++) {
for (int dy = -neighbourhoodSize; dy <= neighbourhoodSize; dy++) {
int dt = t + dx;
int dr = r + dy;
if (dt < 0) dt = dt + maxTheta;
else if (dt >= maxTheta) dt = dt - maxTheta;
if (houghArray[dt*doubleHeight+dr] > peak) {
// found a bigger point nearby, skip
goto loop;
}
}
}
// calculate the true value of theta
double theta = t * thetaStep;
// add the line to the vector
line l={theta, (double)r-houghHeight};
lines.push_back(l);
}
loop:
continue;
}
}
delete[] houghArray;
delete[] sinCache;
delete[] cosCache;
return lines;
}
void binarizeBitmapPart(uint8_t* inPixels, unsigned char* outPixels, size_t width, size_t height, size_t inBytesPerRow, size_t outBytesPerRow){
uint32_t histogram[256]={0};
uint32_t intensitySum=0;
for(unsigned int y=0;y<height;y++){
for(unsigned int x=0;x<width;x++){
uint8_t *px = inPixels + (inBytesPerRow * y) + x * 4;
uint8_t r = *(px + 1);
uint8_t g = *(px + 2);
uint8_t b = *(px + 3);
int l = (r + g + b)/3.0;
outPixels[(outBytesPerRow * y) + x]=l;
histogram[l]++;
intensitySum+=l;
}
}
int threshold=0;
double best_sigma = 0.0;
int first_class_pixel_count = 0;
int first_class_intensity_sum = 0;
for (int thresh = 0; thresh < 255; ++thresh) {
first_class_pixel_count += histogram[thresh];
first_class_intensity_sum += thresh * histogram[thresh];
double first_class_prob = first_class_pixel_count / (double) (width*height);
double second_class_prob = 1.0 - first_class_prob;
double first_class_mean = first_class_intensity_sum / (double) first_class_pixel_count;
double second_class_mean = (intensitySum - first_class_intensity_sum)
/ (double) ((width*height) - first_class_pixel_count);
double mean_delta = first_class_mean - second_class_mean;
double sigma = first_class_prob * second_class_prob * mean_delta * mean_delta;
if (sigma > best_sigma) {
best_sigma = sigma;
threshold = thresh;
}
}
for(unsigned int y=0;y<height;y++){
for(unsigned int x=0;x<width;x++){
uint8_t *px = inPixels + (inBytesPerRow * y) + x * 4;
uint8_t r = *(px + 1);
uint8_t g = *(px + 2);
uint8_t b = *(px + 3);
outPixels[(outBytesPerRow * y) + x]=(r<threshold && g<threshold && b<threshold) ? (unsigned char)255 : (unsigned char)0;
}
}
}
}
NSDictionary *findCornerPoints(UIImage *bitmap) {
CGImageRef imageRef = bitmap.CGImage;
uint32_t width = (uint32_t)CGImageGetWidth(imageRef);
uint32_t height = (uint32_t)CGImageGetHeight(imageRef);
struct ocr::image imgIn, imgOut;
imgIn.width = imgOut.width = width;
imgIn.height = imgOut.height = height;
imgIn.pixel_data = (uint8_t *)malloc(width * height);
imgOut.pixel_data = (uint8_t *)calloc(width * height, 1);
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
uint8_t *bitmapPixels = (uint8_t *)calloc(height * width * 4, sizeof(unsigned char));
NSUInteger bytesPerPixel = 4;
NSUInteger bytesPerRow = bytesPerPixel * width;
NSUInteger bitsPerComponent = 8;
CGContextRef context = CGBitmapContextCreate(bitmapPixels, width, height, bitsPerComponent, bytesPerRow, colorSpace, kCGImageAlphaPremultipliedLast | kCGBitmapByteOrder32Big);
CGColorSpaceRelease(colorSpace);
CGContextDrawImage(context, CGRectMake(0, 0, width, height), imageRef);
CGContextRelease(context);
for(unsigned int y=0;y<height;y++){
for(unsigned int x=0;x<width;x++){
uint32_t px = bitmapPixels[(bytesPerRow * y) + x];
imgIn.pixel_data[width*y+x]=(unsigned char) (((px & 0xFF) + ((px & 0xFF00) >> 8) + ((px & 0xFF0000) >> 16))/3);
}
}
ocr::canny_edge_detect(&imgIn, &imgOut);
std::vector<ocr::line> lines=ocr::detectLines(&imgOut, 100);
for(NSUInteger i = 0; i < width * height; i++) {
imgOut.pixel_data[i]/=2;
}
std::vector<std::vector<ocr::line>> parallelGroups;
for(int i = 0; i < 36; i++) {
parallelGroups.emplace_back();
}
ocr::line *left = NULL;
ocr::line *right = NULL;
ocr::line *top = NULL;
ocr::line *bottom = NULL;
for(std::vector<ocr::line>::iterator l = lines.begin(); l!= lines.end();) {
// remove lines at irrelevant angles
if(!(l->theta>M_PI*0.4 && l->theta<M_PI*0.6) && !(l->theta<M_PI*0.1 || l->theta>M_PI*0.9)){
l=lines.erase(l);
continue;
}
// remove vertical lines close to the middle of the image
if((l->theta<M_PI*0.1 || l->theta>M_PI*0.9) && (uint32_t)abs((int)l->r) < height / 4){
l=lines.erase(l);
continue;
}
// find the leftmost and rightmost lines
if(l->theta<M_PI*0.1 || l->theta>M_PI*0.9){
double rk=l->theta<0.5 ? 1.0 : -1.0;
if(!left || left->r>l->r*rk){
left=&*l;
}
if(!right || right->r<l->r*rk){
right=&*l;
}
}
// group parallel-ish lines with 5-degree increments
parallelGroups[(uint32_t)floor(l->theta / M_PI * 36)].push_back(*l);
++l;
}
// the text on the page tends to produce a lot of parallel lines - so we assume the top & bottom edges of the page
// are topmost & bottommost lines in the largest group of horizontal lines
std::vector<ocr::line>& largestParallelGroup=parallelGroups[0];
for(std::vector<std::vector<ocr::line>>::iterator group=parallelGroups.begin();group!=parallelGroups.end();++group){
if(largestParallelGroup.size()<group->size())
largestParallelGroup=*group;
}
for(std::vector<ocr::line>::iterator l=largestParallelGroup.begin();l!=largestParallelGroup.end();++l){
// If the image is horizontal, we assume it's just the data page or an ID card so we're going for the topmost line.
// If it's vertical, it likely contains both the data page and the page adjacent to it so we're going for the line that is closest to the center of the image.
// Nobody in their right mind is going to be taking vertical pictures of ID cards, right?
if(width>height){
if(!top || top->r>l->r){
top=&*l;
}
}else{
if(!top || fabs(l->r)<fabs(top->r)){
top=&*l;
}
}
if(!bottom || bottom->r<l->r){
bottom=&*l;
}
}
bool foundTopLeft=false, foundTopRight=false, foundBottomLeft=false, foundBottomRight=false;
NSMutableDictionary *points = [[NSMutableDictionary alloc] init];
if(top && bottom && left && right){
//LOGI("bottom theta %f", bottom->theta);
if(bottom->theta>1.65 || bottom->theta<1.55){
//LOGD("left: %f, right: %f\n", left->r, right->r);
double centerX=width/2.0;
double centerY=height/2.0;
double ltsin=sin(left->theta);
double ltcos=cos(left->theta);
double rtsin=sin(right->theta);
double rtcos=cos(right->theta);
double ttsin=sin(top->theta);
double ttcos=cos(top->theta);
double btsin=sin(bottom->theta);
double btcos=cos(bottom->theta);
for (int y = -((int)height)/4; y < (int)height; y++) {
int lx = (int) (((left->r - ((y - centerY) * ltsin)) / ltcos) + centerX);
int ty = (int) (((top->r - ((lx - centerX) * ttcos)) / ttsin) + centerY);
if(ty==y){
points[@0]=@(lx);
points[@1]=@(y);
foundTopLeft=true;
if(foundTopRight)
break;
}
int rx = (int) (((right->r - ((y - centerY) * rtsin)) / rtcos) + centerX);
ty = (int) (((top->r - ((rx - centerX) * ttcos)) / ttsin) + centerY);
if(ty==y){
points[@2]=@(rx);
points[@3]=@(y);
foundTopRight=true;
if(foundTopLeft)
break;
}
}
for (int y = height+height/3; y>=0; y--) {
int lx = (int) (((left->r - ((y - centerY) * ltsin)) / ltcos) + centerX);
int by = (int) (((bottom->r - ((lx - centerX) * btcos)) / btsin) + centerY);
if(by==y){
points[@4]=@(lx);
points[@5]=@(y);
foundBottomLeft=true;
if(foundBottomRight)
break;
}
int rx = (int) (((right->r - ((y - centerY) * rtsin)) / rtcos) + centerX);
by = (int) (((bottom->r - ((rx - centerX) * btcos)) / btsin) + centerY);
if(by==y){
points[@6]=@(rx);
points[@7]=@(y);
foundBottomRight=true;
if(foundBottomLeft)
break;
}
}
}else{
//LOGD("No perspective correction needed");
}
}
free(imgIn.pixel_data);
free(imgOut.pixel_data);
if(foundTopLeft && foundTopRight && foundBottomLeft && foundBottomRight) {
return points;
}
return nil;
}
NSArray *binarizeAndFindCharacters(UIImage *inBmp, UIImage **outBinaryImage) {
CGImageRef imageRef = inBmp.CGImage;
uint32_t width = (uint32_t)CGImageGetWidth(imageRef);
uint32_t height = (uint32_t)CGImageGetHeight(imageRef);
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
uint8_t *bitmapPixels = (uint8_t *)calloc(height * width * 4, sizeof(unsigned char));
NSUInteger bytesPerPixel = 4;
NSUInteger bytesPerRow = bytesPerPixel * width;
NSUInteger bitsPerComponent = 8;
CGContextRef context = CGBitmapContextCreate(bitmapPixels, width, height, bitsPerComponent, bytesPerRow, colorSpace, kCGImageAlphaNoneSkipFirst);
CGColorSpaceRelease(colorSpace);
CGContextDrawImage(context, CGRectMake(0, 0, width, height), imageRef);
CGContextRelease(context);
uint8_t *outPixels = (uint8_t *)malloc(width * height * 1);
// uint32_t histogram[256]={0};
// uint32_t intensitySum=0;
// for(unsigned int y=0;y<height;y++){
// for(unsigned int x=0;x<width;x++){
// uint8_t *px = bitmapPixels + (bytesPerRow * y) + x * 4;
// uint8_t r = *(px + 1);
// uint8_t g = *(px + 2);
// uint8_t b = *(px + 3);
// int l = (r + g + b)/3.0;
// outPixels[(width * y) + x]=l;
// histogram[l]++;
// intensitySum+=l;
// }
// }
// uint32_t threshold=0;
// double best_sigma = 0.0;
//
// int first_class_pixel_count = 0;
// int first_class_intensity_sum = 0;
//
// for (int thresh = 0; thresh < 255; ++thresh) {
// first_class_pixel_count += histogram[thresh];
// first_class_intensity_sum += thresh * histogram[thresh];
//
// double first_class_prob = first_class_pixel_count / (double) (width*height);
// double second_class_prob = 1.0 - first_class_prob;
//
// double first_class_mean = first_class_intensity_sum / (double) first_class_pixel_count;
// double second_class_mean = (intensitySum - first_class_intensity_sum) / (double) ((width*height) - first_class_pixel_count);
//
// double mean_delta = first_class_mean - second_class_mean;
// double sigma = first_class_prob * second_class_prob * mean_delta * mean_delta;
//
// if (sigma > best_sigma) {
// best_sigma = sigma;
// threshold = thresh;
// }
// }
//
// for(unsigned int y=0;y<height;y++){
// for(unsigned int x=0;x<width;x++){
// uint8_t *px = bitmapPixels + (bytesPerRow * y) + x * 4;
// uint8_t r = *(px + 1);
// uint8_t g = *(px + 2);
// uint8_t b = *(px + 3);
// outPixels[(width * y) + x]=(r<threshold && g<threshold && b<threshold) ? (unsigned char)255 : (unsigned char)0;
// }
// }
for(unsigned int y=0;y<height;y+=120){
for(unsigned int x=0; x<width; x+=120){
int partWidth=x+120<width ? 120 : (width-x);
int partHeight=y+120<height ? 120 : (height-y);
ocr::binarizeBitmapPart((bitmapPixels + (y * bytesPerRow) + x * 4), outPixels + (width * y) + x, partWidth, partHeight, bytesPerRow, width);
}
}
// remove any single pixels without adjacent ones - these are usually noise
for(unsigned int y=height/2;y<height-1;y++){
unsigned int yOffset=y*width;
unsigned int yOffsetPrev=(y-1)*width;
unsigned int yOffsetNext=(y+1)*width;
for(unsigned int x=1;x<width-1;x++){
int pixelCount=0;
if(outPixels[yOffsetPrev+x-1]!=0)
pixelCount++;
if(outPixels[yOffsetPrev+x]!=0)
pixelCount++;
if(outPixels[yOffsetPrev+x+1]!=0)
pixelCount++;
if(outPixels[yOffset+x-1]!=0)
pixelCount++;
if(outPixels[yOffset+x]!=0)
pixelCount++;
if(outPixels[yOffset+x+1]!=0)
pixelCount++;
if(outPixels[yOffsetNext+x-1]!=0)
pixelCount++;
if(outPixels[yOffsetNext+x]!=0)
pixelCount++;
if(outPixels[yOffsetNext+x+1]!=0)
pixelCount++;
if(pixelCount<3)
outPixels[yOffset+x]=0;
}
}
if (outBinaryImage != nil)
{
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceGray();
CGContextRef context = CGBitmapContextCreate(outPixels, width, height, 8, width, colorSpace, kCGImageAlphaNone);
CGColorSpaceRelease(colorSpace);
CGImageRef imgRef = CGBitmapContextCreateImage(context);
UIImage *img = [UIImage imageWithCGImage:imgRef];
CGImageRelease(imgRef);
CGContextRelease(context);
*outBinaryImage = img;
}
// search from the bottom up for continuous areas of mostly empty pixels
unsigned int consecutiveEmptyRows=0;
std::vector<std::pair<unsigned int, unsigned int>> emptyAreaYs;
for(unsigned int y=height-1;y>=height/2;y--){
unsigned int consecutiveEmptyPixels=0;
unsigned int maxEmptyPixels=0;
for(unsigned int x=0;x<width;x++){
if(outPixels[width * y + x]==0){
consecutiveEmptyPixels++;
}else{
maxEmptyPixels=max(maxEmptyPixels, consecutiveEmptyPixels);
consecutiveEmptyPixels=0;
}
}
maxEmptyPixels=max(maxEmptyPixels, consecutiveEmptyPixels);
if(maxEmptyPixels>width/10*8){
consecutiveEmptyRows++;
}else if(consecutiveEmptyRows>0){
emptyAreaYs.emplace_back(y, y+consecutiveEmptyRows);
consecutiveEmptyRows=0;
}
}
NSMutableArray *result = [[NSMutableArray alloc] init];
// using the areas found above, do the same thing but horizontally and between them in an attempt to ultimately find the bounds of the MRZ characters
for(std::vector<std::pair<unsigned int, unsigned int>>::iterator p=emptyAreaYs.begin();p!=emptyAreaYs.end();++p){
std::vector<std::pair<unsigned int, unsigned int>>::iterator next=std::next(p);
if(next!=emptyAreaYs.end()){
unsigned int lineHeight=p->first-next->second;
// An MRZ line can't really be this thin so this probably isn't one
if(lineHeight<10)
continue;
unsigned int consecutiveEmptyCols=0;
std::vector<std::pair<unsigned int, unsigned int>> emptyAreaXs;
for(unsigned int x=0;x<width;x++){
unsigned int consecutiveEmptyPixels=0;
unsigned int maxEmptyPixels=0;
unsigned int bottomFilledPixels=0; // count these separately because we want those L's recognized correctly
for(unsigned int y=next->second;y<p->first;y++){
if(outPixels[width * y + x]==0){
consecutiveEmptyPixels++;
}else{
maxEmptyPixels=max(maxEmptyPixels, consecutiveEmptyPixels);
consecutiveEmptyPixels=0;
if(y>p->first-3)
bottomFilledPixels++;
}
}
maxEmptyPixels=consecutiveEmptyPixels;
if(lineHeight-maxEmptyPixels<=lineHeight/15 && bottomFilledPixels==0){
consecutiveEmptyCols++;
}else if(consecutiveEmptyCols>0){
emptyAreaXs.emplace_back(x-consecutiveEmptyCols, x);
consecutiveEmptyCols=0;
}
}
if(consecutiveEmptyCols>0){
emptyAreaXs.emplace_back(width-consecutiveEmptyCols, width);
}
if(emptyAreaXs.size()>30){
bool foundLeftPadding=false;
NSMutableArray *rects = [[NSMutableArray alloc] init];
for(std::vector<std::pair<unsigned int, unsigned int>>::iterator h=emptyAreaXs.begin();h!=emptyAreaXs.end();++h){
std::vector<std::pair<unsigned int, unsigned int>>::iterator nextH=std::next(h);
if(!foundLeftPadding && h->second-h->first>width/35){
foundLeftPadding=true;
}else if(foundLeftPadding && h->second-h->first>width/30){
if(rects.count>=30){
break;
}else{
// restart the search because now we've (hopefully) found the real padding
[rects removeAllObjects];
}
}
if(nextH!=emptyAreaXs.end() && foundLeftPadding){
unsigned int top=next->second;
unsigned int bottom=p->first;
// move the top and bottom edges towards each other as part of normalization
for(unsigned int y=top;y<bottom;y++){
bool found=false;
for(unsigned int x=h->second; x<nextH->first; x++){
if(outPixels[width * y + x]!=0){
top=y;
found=true;
break;
}
}
if(found)
break;
}
for(unsigned int y=bottom;y>top;y--){
bool found=false;
for(unsigned int x=h->second; x<nextH->first; x++){
if(outPixels[width * y + x]!=0){
bottom=y;
found=true;
break;
}
}
if(found)
break;
}
if(bottom-top<lineHeight/4)
continue;
if(rects.count < 44){
CGRect rect = CGRectMake(h->second, top, nextH->first - h->second, bottom - top);
[rects addObject:[NSValue valueWithCGRect:rect]];
}
}
}
[result addObject:rects];
if((rects.count>=44 && result.count == 2) || (rects.count>=30 && result.count==3)){
break;
}
}
}
}
free(outPixels);
if(result.count == 0)
return NULL;
return result;
}
NSString *performRecognition(UIImage *bitmap, int numRows, int numCols)
{
NSString *filePath = TGComponentsPathForResource(@"ocr_nn", @"bin");
NSData *nnData = [NSData dataWithContentsOfFile:filePath];
struct genann* ann=genann_init(150, 1, 90, 37);
memcpy(ann->weight, nnData.bytes, sizeof(double)*ann->total_weights);
NSMutableString *res = [[NSMutableString alloc] init];
const char* alphabet="ABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890<";
CGImageRef imageRef = bitmap.CGImage;
uint32_t width = (uint32_t)CGImageGetWidth(imageRef);
uint32_t height = (uint32_t)CGImageGetHeight(imageRef);
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceGray();
uint8_t *bitmapPixels = (uint8_t *)calloc(height * width * 1, sizeof(unsigned char));
NSUInteger bytesPerPixel = 1;
NSUInteger bytesPerRow = bytesPerPixel * width;
NSUInteger bitsPerComponent = 8;
CGContextRef context = CGBitmapContextCreate(bitmapPixels, width, height, bitsPerComponent, bytesPerRow, colorSpace, kCGImageAlphaNone);
CGColorSpaceRelease(colorSpace);
CGContextDrawImage(context, CGRectMake(0, 0, width, height), imageRef);
CGContextRelease(context);
double nnInput[150];
for(int row=0;row<numRows;row++){
for(int col=0;col<numCols;col++){
unsigned int offX=static_cast<unsigned int>(col*10);
unsigned int offY=static_cast<unsigned int>(row*15);
for(unsigned int y=0;y<15;y++){
for(unsigned int x=0;x<10;x++){
nnInput[y*10+x]=(double)bitmapPixels[bytesPerRow * (offY+y) + offX + x]/255.0;
}
}
const double* nnOut=genann_run(ann, nnInput);
unsigned int bestIndex=0;
for(unsigned int i=0;i<37;i++){
if(nnOut[i]>nnOut[bestIndex])
bestIndex=i;
}
[res appendString:[NSString stringWithFormat:@"%c", alphabet[bestIndex]]];
}
if(row!=numRows-1)
[res appendString:@"\n"];
}
genann_free(ann);
return res;
}
UIImage *normalizeImage(UIImage *image)
{
if (image.imageOrientation == UIImageOrientationUp) return image;
UIGraphicsBeginImageContextWithOptions(image.size, NO, image.scale);
[image drawInRect:CGRectMake(0, 0, image.size.width, image.size.height)];
UIImage *normalizedImage = UIGraphicsGetImageFromCurrentImageContext();
UIGraphicsEndImageContext();
return normalizedImage;
}
NSString *recognizeMRZ(UIImage *input, CGRect *outBoundingRect)
{
input = normalizeImage(input);
UIImage *binaryImage;
NSArray *charRects = binarizeAndFindCharacters(input, &binaryImage);
if (charRects.count == 0)
return nil;
uint32_t width = 10 * (int)[charRects.firstObject count];
uint32_t height = 15 * (int)charRects.count;
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceGray();
CGContextRef context = CGBitmapContextCreate(NULL, width, height, 8, width, colorSpace, kCGImageAlphaNone);
CGColorSpaceRelease(colorSpace);
int x, y = 0;
for (NSArray *line in charRects)
{
x = 0;
for (NSValue *v in line)
{
CGRect rect = v.CGRectValue;
CGRect dest = CGRectMake(x * 10, y * 15, 10, 15);
CGImageRef charImage = CGImageCreateWithImageInRect(binaryImage.CGImage, rect);
CGContextDrawImage(context, dest, charImage);
CGImageRelease(charImage);
x++;
}
y++;
}
CGImageRef charsImageRef = CGBitmapContextCreateImage(context);
CGContextRelease(context);
UIImage *charsImage = [UIImage imageWithCGImage:charsImageRef];
CGImageRelease(charsImageRef);
NSString *result = performRecognition(charsImage, (int)charRects.count, (int)[charRects.firstObject count]);
if (result != nil && outBoundingRect != NULL)
{
CGRect firstRect = [[charRects.firstObject firstObject] CGRectValue];
firstRect.origin.y = input.size.height - firstRect.origin.y;
CGRect lastRect = [[charRects.lastObject lastObject] CGRectValue];
lastRect.origin.y = input.size.height - lastRect.origin.y;
CGRect boundingRect = CGRectMake(CGRectGetMinX(firstRect), CGRectGetMinY(firstRect), CGRectGetMaxX(lastRect) - CGRectGetMinX(firstRect), CGRectGetMaxY(lastRect) - CGRectGetMinY(firstRect));
*outBoundingRect = boundingRect;
}
return result;
}