opencv2.x 以上 删除二值化图像中面积较小的区域

Mat remove_block(double minarea, Mat& src){CvSeq* contour = NULL;double tmparea = 0.0;CvMemStorage* storage = cvCreateMemStorage(0);//const char* tmpaddsum1 = tmp_string.c_str();//IplImage* img_src = cvLoadImage(tmpaddsum1, CV_LOAD_IMAGE_ANYCOLOR);IplImage* img_src = &IplImage(src);IplImage* img_Clone = cvCloneImage(img_src);//访问二值图像每个点的值uchar *pp;IplImage* img_dst = cvCreateImage(cvGetSize(img_src), IPL_DEPTH_8U, 1);//-----搜索2值图中的轮廓，并从轮廓树中删除面积小于minarea的区域-----////CvScalar color = cvScalar(255, 0, 0);//CV_RGB(128,0,0)CvContourScanner scanner = NULL;scanner = cvStartFindContours(img_src, storage, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_NONE, cvPoint(0, 0));//开始遍历轮廓树CvRect rect;while (contour = cvFindNextContour(scanner)){tmparea = fabs(cvContourArea(contour));rect = cvBoundingRect(contour, 0);if (tmparea < minarea){//当连通区域的中心点为白色时，而且面积较小则用黑色进行填充pp = (uchar*)(img_Clone->imageData + img_Clone->widthStep*(rect.y + rect.height / 2) + rect.x + rect.width / 2);if (pp[0] == 255){for (int y = rect.y; y<rect.y + rect.height; y++){for (int x = rect.x; x<rect.x + rect.width; x++){pp = (uchar*)(img_Clone->imageData + img_Clone->widthStep*y + x);if (pp[0] == 255){pp[0] = 0;}}}}}}Mat dst_img = cvarrToMat(img_Clone);if (dst_img.channels()==3)cvtColor(dst_img,dst_img,CV_RGB2GRAY);return dst_img;}