UIImage * image = [UIImage imageNamed:@"abc.png"];//將UIImage轉換成Matcv::Mat resultImage;UIImageToMat(image, resultImage);//轉為灰度圖cvtColor(resultImage, resultImage, 6);//利用閾值二值化cv::threshold(resultImage, resultImage, 100, 255, CV_THRESH_BINARY);//腐蝕，填充（腐蝕是讓黑色點變大）cv::Mat erodeElement = getStructuringElement(cv::MORPH_RECT, cv::Size(140,140)); cv::erode(resultImage, resultImage, erodeElement);//輪廊檢測std::vector> contours;//定義一個容器來存儲所有檢測到的輪廊cv::findContours(resultImage, contours, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cvPoint(0, 0));//取出身份證號碼區域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(@"位置分別為:x=%d,y=%d,width=%d,height%d",rect.x,rect.y,rect.width,rect.height);//算法原理：如果新的區域范圍寬度大于已賦值區域寬度，并且寬度為高度的五倍則賦予新值    if (rect.width > numberRect.width && rect.width > rect.height * 5 && rect.height > 200 && rect.height < 300) {    numberRect = rect;    }}//定位成功成功，去原圖截取身份證號碼區域，并轉換成灰度圖、進行二值化處理cv::Mat matImage;UIImageToMat(image, matImage);resultImage = matImage(numberRect);cvtColor(resultImage, resultImage, cv::COLOR_BGR2GRAY);cv::threshold(resultImage, resultImage, 80, 255, CV_THRESH_BINARY);//將Mat轉換成UIImageUIImage *numberImage = MatToUIImage(resultImage);