通过形态学操作实现图像边缘

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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