通过形态学操作实现图像边缘

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实现图像边缘的算法的思路是：首先将图像转换为二值图像，然后膨胀此二值图像，最后减去未膨胀之前的图像便得到了图像的边缘。

参考代码如下所示：

int _tmain(int argc, _TCHAR* argv[]){    IplImage *srcImg = cvLoadImage("test.jpg");    IplImage *grayImg = cvCreateImage(cvGetSize(srcImg), 8, 1);    cvCvtColor(srcImg, grayImg, CV_BGR2GRAY);        IplImage *dstImg = cvCreateImage(cvGetSize(srcImg), 8, 1);cvThreshold(grayImg, dstImg, cv::Otsu(srcImg), 255, CV_THRESH_BINARY);        IplConvKernel *kernel = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_CROSS);    cvMorphologyEx(dstImg, dstImg, NULL, kernel, CV_MOP_OPEN, 3);    cvMorphologyEx(dstImg, dstImg, NULL, kernel, CV_MOP_CLOSE, 1);    // Find edges: dilate(image) - image;    IplImage *dilatedImg = cvCreateImage(cvGetSize(srcImg), 8, 1);    cvDilate(dstImg, dilatedImg, kernel, 1);    cvSub(dilatedImg, dstImg, dstImg);    // Label edges in srcImg     IplImage *redCh = cvCreateImage(cvGetSize(srcImg), 8, 1);    IplImage *greenCh = cvCreateImage(cvGetSize(srcImg), 8, 1);    IplImage *blueCh = cvCreateImage(cvGetSize(srcImg), 8, 1);    cvSplit(srcImg, blueCh, greenCh, redCh, NULL);    cvOr(redCh, dstImg, redCh);    cvMerge(blueCh, greenCh, redCh, NULL, srcImg);    cvNamedWindow("src");    cvShowImage("src", srcImg);    cvNamedWindow("dst");    cvShowImage("dst", dstImg);    cvWaitKey(0);    return 0;}

其中cv::Otsu(srcImg)的算法，可参考http://en.wikipedia.org/wiki/Otsu%27s_method

输出结果：

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