1、利用 at 函数读取
(1)单通道图像读取方式
Mat img1 = imread(filename,IMREAD_GRAYSCALE); for( size_t nrow = 0; nrow < img1.rows; nrow++) { for(size_t ncol = 0; ncol < img1.cols; ncol++) { uchar val = mat_CV_8UC1.at<uchar>(nrow,ncol); } }
(2) 三通道图像读取方式
Mat img2 = imread(filename,IMREAD_COLOR); for( size_t nrow = 0; nrow < img2.rows; nrow++) { for(size_t ncol = 0; ncol < img2.cols; ncol++) { Vec3i bgr = mat_CV_8UC3.at<Vec3b>(nrow,ncol);//用Vec3b也行 cout << "("<<bgr.val[0]<<"," <<bgr.val[1]<<"," <<bgr.val[2]<<")"; } cout << endl; }
2、使用指针读取
for( size_t nrow = 0; nrow < img3.rows; nrow++) { uchar* data = img3.ptr<uchar>(nrow); for(size_t ncol = 0; ncol < img3.cols * img3.channels(); ncol++) { cout << int( data[ncol] ) ; } cout << endl; }
3、使用迭代器
Mat img4 = imread(filename,IMREAD_GRAYSCALE); MatIterator_<uchar> it = img4.begin<uchar>(), it_end = img4.end<uchar>(); for(int cnt = 1; it != it_end; ++it) { cout << ( int(*it) ) ; if( (cnt++ % img4.cols) ==0 ) cout << endl; }
4、使用矩阵元素的地址定位知识
Mat img5(rows, cols,CV_8U, Scalar(0)); for( size_t nrow = 0; nrow < img5.rows; nrow++) for(size_t ncol = 0; ncol < img5.cols; ncol++) { cout<<(int)(*(img5.data+img5.step[0]*nrow+img5.step[1]*ncol)); }
5、补充:在使用 at 函数的情况下需要预先知道Mat变量中存储的元素类型,如果类型不匹配就会出现读错误。所以可以采用c++ boost库中的BOOST_TYPEOF来获取图像的元素数据类型。例:
Mat img6 = imread(filename); typedef BOOST_TYPEOF(*img6.data) ElementType for( size_t nrow = 0; nrow < img1.rows; nrow++) { for(size_t ncol = 0; ncol < img1.cols; ncol++) { cout<<mat_CV_8UC1.at<ElementType>(nrow,ncol); } }
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标签:Mat,nrow,++,cols,Opencv,ncol,size,读取 From: https://www.cnblogs.com/rainbow70626/p/17725623.html