opencv对手写数字进行无黏连切割

//src：待分割的二值图，最大值为255
//segMat：分割好的每个图片
//算法：判断连通域，有几个连通域就会分割成几个子图片
//用途：手写数字识别中进行无黏连数字的分割
void getConnectedDomain(cv::Mat &src, vector<cv::Mat>& segMat)//segMat为最终结果，存放分割好的每个数字
{
    int img_row = src.rows;
    int img_col = src.cols;
    cv::Mat flag = cv::Mat::zeros(cv::Size(img_col, img_row), CV_8UC1);//标志矩阵，为0则当前像素点未访问过

    for (int i = ; i < img_row; i++)
    {
        for (int j = ; j < img_col; j++)
        {
            if (src.ptr<uchar>(i)[j] ==  && flag.ptr<uchar>(i)[j] == )
            {
                cv::Mat subMat = cv::Mat::zeros(cv::Size(img_col, img_row), CV_8UC1);//表明子图
                stack<cv::Point2f> cd;
                cd.push(cv::Point2f(j, i));
                flag.ptr<uchar>(i)[j] = ;
                subMat.ptr<uchar>(i)[j] = ;

                while (!cd.empty())
                {
                    cv::Point2f tmp = cd.top();

                    cd.pop();
                    cv::Point2f p[];//邻域像素点，这里用的四邻域
                    p[] = cv::Point2f(tmp.x -  >  ? tmp.x -  : , tmp.y);
                    p[] = cv::Point2f(tmp.x +  < img_col -  ? tmp.x +  : img_row - , tmp.y);
                    p[] = cv::Point2f(tmp.x, tmp.y -  >  ? tmp.y -  : );
                    p[] = cv::Point2f(tmp.x, tmp.y +  < img_row -  ? tmp.y +  : img_row - );
                    for (int m = ; m < ; m++)
                    {
                        int x = p[m].y;
                        int y = p[m].x;
                        if (src.ptr<uchar>(x)[y] ==  && flag.ptr<uchar>(x)[y] == )//如果未访问，则入栈，并标记访问过该点
                        {
                            cd.push(p[m]);
                            flag.ptr<uchar>(x)[y] = ;
                            subMat.ptr<uchar>(x)[y] = ;
                        }
                    }
                }
                segMat.push_back(subMat);
            }
        }
    }
}