UIImage * image = [UIImage imageNamed:@"abc.png"];//將UIImage轉(zhuǎn)換成Matcv::Mat resultImage;UIImageToMat(image, resultImage);//轉(zhuǎn)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(diǎn)變大）cv::Mat erodeElement = getStructuringElement(cv::MORPH_RECT, cv::Size(140,140)); cv::erode(resultImage, resultImage, erodeElement);//輪廊檢測(cè)std::vector> contours;//定義一個(gè)容器來(lái)存儲(chǔ)所有檢測(cè)到的輪廊cv::findContours(resultImage, contours, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cvPoint(0, 0));//取出身份證號(hào)碼區(qū)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(qū)域范圍寬度大于已賦值區(qū)域?qū)挾龋⑶覍挾葹楦叨鹊奈灞秳t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(hào)碼區(qū)域，并轉(zhuǎn)換成灰度圖、進(jìn)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(zhuǎn)換成UIImageUIImage *numberImage = MatToUIImage(resultImage);