UIImage * image = [UIImage imageNamed:@"abc.png"];

//将UIImage转换成Matcv::Mat resultImage;

UIImageToMat(image, resultImage);

//转为灰度图

cvtColor(resultImage, resultImage, 6);

//利用阈值二值化

cv::threshold(resultImage, resultImage, 100, 255, CV_THRESH_BINARY);

//腐蚀，填充（腐蚀是让黑色点变大）

cv::Mat erodeElement = getStructuringElement(cv::MORPH_RECT, cv::Size(140,140)); 

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));

//取出身份证号码区域

std::vectorrects;cv::Rect numberRect = cv::Rect(0,0,0,0); std::vector>::const_iterator itContours = contours.begin();

for ( ; itContours != contours.end(); ++itContours) {

cv::Rect rect = cv::boundingRect(*itContours);

rects.push_back(rect);

NSLog(@"位置分别为:x=%d,y=%d,width=%d,height%d",rect.x,rect.y,rect.width,rect.height);

//算法原理：如果新的区域范围宽度大于已赋值区域宽度，并且宽度为高度的五倍则赋予新值

    if (rect.width > numberRect.width && rect.width > rect.height * 5 && rect.height > 200 && rect.height < 300) {

    numberRect = 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

cv::Mat matImage;

UIImageToMat(image, matImage);

resultImage = matImage(numberRect);

cvtColor(resultImage, resultImage, cv::COLOR_BGR2GRAY);

cv::threshold(resultImage, resultImage, 80, 255, CV_THRESH_BINARY);

//将Mat转换成UIImage

UIImage *numberImage = MatToUIImage(resultImage);