第一次写简书，多见谅。
本文运用opencv+TesseractOCR来实现身份证识别姓名和身份证号
查阅并引用了很多文章
opencv安装及入门
OpenCV在iOS上的应用尝试
在身份证识别上，由于相机拍摄的亮度及其他问题难点在于图片的阈值二值化的判断，用过固定阈值二值化、局部阈值二值化、平均阈值二值化都不理想。
在基于opencv的一种局部自适应快速二值化方法（积分法）文章中方法解决了光照不均匀的图像中进行二值化。
//扫描身份证图片，并进行预处理，定位号码区域图片并返回
- (NSArray*)opencvScanCard:(UIImage*)image {
//将UIImage转换成Mat
cv::MatresultImage;
UIImageToMat(image, resultImage);
//先用使用3x3内核来降噪
blur( resultImage, resultImage,cv::Size(3,3),cv::Point(-1,-1));
//UIImage *Image2 = MatToUIImage(resultImage);
////固定阈值二值化
//cv::threshold(resultImage, resultImage, 100, 255, CV_THRESH_BINARY);
////局部阈值二值化
//cv::adaptiveThreshold(resultImage, resultImage, 255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY, 3, 5);
////平均阈值二值化
//IplImage imgTopDown = resultImage;
//CvScalar mean ,std_dev;//平均值、标准差
//double u_threshold,d_threshold;
//cvAvgSdv(&imgTopDown,&mean,&std_dev,NULL);
//u_threshold = mean.val[0] +1.5* std_dev.val[0];//上阀值
//d_threshold = mean.val[0] -1.5* std_dev.val[0];//下阀值
//u_threshold = mean.val[0];
//d_threshold = mean.val[0];
////u_threshold = mean + 2.5 * std_dev; //错误
////d_threshold = mean - 2.5 * std_dev;
//std::cout<<"The TopThreshold of this Image in TopDown is:"<
//std::cout<<"The DownThreshold of this Image in TopDown is:"<
//cv::threshold(resultImage,resultImage,d_threshold,u_threshold,CV_THRESH_BINARY);//上下阀值
//积分阈值二值化
resultImage =AdaptiveThereshold(resultImage, resultImage);
//腐蚀，填充（腐蚀是让黑色点变大）
cv::MaterodeElement =getStructuringElement(cv::MORPH_RECT,cv::Size(22,22));
cv::erode(resultImage, resultImage, erodeElement);
//轮廊检测
std::vector> contours;//定义一个容器来存储所有检测到的轮廊
cv::findContours(resultImage, contours,CV_RETR_TREE,CV_CHAIN_APPROX_SIMPLE,cvPoint(0,0));
//cv::drawContours(resultImage, contours, -1, cv::Scalar(255),4);
//取出身份证号码区域
std::vector rects;
cv::RectNameNumberRect =cv::Rect(0,0,0,0);
cv::RectCardNumberRect =cv::Rect(0,0,0,0);
std::vector>::const_iteratoritContours = contours.begin();
for( ; itContours != contours.end(); ++itContours) {
cv::Rectrect =cv::boundingRect(*itContours);
rects.push_back(rect);
//算法原理
if(rect.width> CardNumberRect.width&& rect.width> rect.height*6) {
CardNumberRect = rect;
}
if(rect.x>60&& rect.y<120&& rect.height*2< rect.width) {
NameNumberRect = rect;
}
}
//定位成功成功，去原图截取身份证号码区域，并转换成灰度图、进行二值化处理
//去原图截取身份证姓名区域，并转换成灰度图、进行二值化处理
cv::MatmatImage;
UIImageToMat(image, matImage);
cv::MatNameImageMat;
NameImageMat = matImage(NameNumberRect);
IplImagegrey = NameImageMat;
unsignedchar* dataImage = (unsignedchar*)grey.imageData;
intthreshold =Otsu(dataImage, grey.width, grey.height);
printf("阈值：%d\n",threshold);
NameImageMat =AdaptiveThereshold(NameImageMat, NameImageMat);
UIImage*NameImage =MatToUIImage(NameImageMat);
cv::MatCardImageMat;
CardImageMat = matImage(CardNumberRect);
CardImageMat =AdaptiveThereshold(CardImageMat, CardImageMat);
UIImage*CardImage =MatToUIImage(CardImageMat);
//身份证号码定位失败
if([publicClassobjectIsEmpty:CardImage]||[publicClassobjectIsEmpty:NameImage]) {
returnnil;
}
NSArray* arr =@[NameImage,CardImage];
returnarr;
}
局部自适应快速积分二值化方法
cv::Mat AdaptiveThereshold(cv::Mat src,cv::Mat dst)
{
cvtColor(src,dst,CV_BGR2GRAY);
int x1, y1, x2, y2;
int count=0;
long long sum=0;
int S=src.rows>>3; //划分区域的大小S*S
int T=15; /*百分比，用来最后与阈值的比较。原文：If the value of the current pixel is t percent less than this average
then it is set to black, otherwise it is set to white.*/
int W=dst.cols;
int H=dst.rows;
long long **Argv;
Argv=new long long*[dst.rows];
for(int ii=0;ii<dst.rows;ii++)
{
Argv[ii]=new long long[dst.cols];
}
for(int i=0;i<W;i++)
{
sum=0;
for(int j=0;j<H;j++)
{
sum+=dst.at<uchar>(j,i);
if(i==0)
Argv[j][i]=sum;
else
Argv[j][i]=Argv[j][i-1]+sum;
}
}
for(int i=0;i<W;i++)
{
for(int j=0;j<H;j++)
{
x1=i-S/2;
x2=i+S/2;
y1=j-S/2;
y2=j+S/2;
if(x1<0)
x1=0;
if(x2>=W)
x2=W-1;
if(y1<0)
y1=0;
if(y2>=H)
y2=H-1;
count=(x2-x1)*(y2-y1);
sum=Argv[y2][x2]-Argv[y1][x2]-Argv[y2][x1]+Argv[y1][x1];
if((long long)(dst.at<uchar>(j,i)*count)<(long long)sum*(100-T)/100)
dst.at<uchar>(j,i)=0;
else
dst.at<uchar>(j,i)=255;
}
}
for (int i = 0 ; i < dst.rows; ++i)
{
delete [] Argv[i];
}
delete [] Argv;
return dst;
}
TesseractOCR识别文字
//利用TesseractOCR识别文字
- (void)tesseractRecognizeImageArr:(NSArray *)arr compleate:(CompleateBlock)compleate {
dispatch_async(dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_BACKGROUND, 0), ^{
NSMutableArray* marr = [NSMutableArray array];
for (int i = 0; i<arr.count; i++) {
G8Tesseract *tesseract;
if(i==0){
tesseract = [[G8Tesseract alloc] initWithLanguage:@"chi_sim"];
}else{
tesseract = [[G8Tesseract alloc] initWithLanguage:@"eng"];
}
tesseract.image = [arr[i] g8_blackAndWhite];
tesseract.image = arr[i];
// Start the recognition
[tesseract recognize];
//执行回调
[marr addObject:tesseract.recognizedText];
}
compleate(marr[0],marr[1]);
});
}
参考文章：
iOS身份证号码识别
demo下载：
由于包含字体库，demo比较大，还有下载完后请自行pod install。
idCardOpencv
