基于opencv的角点检测

转自：http://blog.sina.com.cn/s/blog_5d793ffc0100fxq4.html

OpenCV角点检测小结

1，cvGoodFeaturesToTrack，cvCornerMinEigenVal，CornerEigenValsAndVecs是一类，用到了图像差分的相关矩阵。

2，CornerHarris，利用CornerEigenValsAndVecs得到的图像差分相关矩阵，据其特征值和向量，判断角点， Harris角点探测器R（x，y）=det（M）-k*trace^2(M)

3，FindCornerSubPix，子象素级角点定位的实现是基于对向量正交性的观测而实现的。貌似适合棋盘格特征点检测，有待研究。

4，cvPreCornerDetect，计算一个二阶导多项式，角点被认为是函数的局部最大值。其实就是K-R法，利用了梯度的变化率在边缘走 向的投影能反映尖锐程度。试验发现是一种比cvGoodFeaturesToTrack粗略的办法。

注意：1，2，4都是检测像素级的角点。

#include "stdafx.h"
#include "cv.h"
#include "highgui.h"
#include "cxcore.h"
#define max_corners 500

int _tmain(int argc, _TCHAR* argv[])
{
int cornerCount=max_corners;
CvPoint2D32f corners[max_corners];
double qualityLevel;
double minDistance;
IplImage *srcImage = 0, *grayImage = 0, *corners1 = 0, *corners2 = 0;
int i;
CvScalar color = CV_RGB(255,0,0);

cvNamedWindow( "image", 1 ); // create HighGUI window with name "image"

//Load the image to be processed
srcImage = cvLoadImage("D://zero//VasoR.bmp",1);

grayImage = cvCreateImage(cvGetSize(srcImage), IPL_DEPTH_8U, 1);

//copy the source image to copy image after converting the format
cvCvtColor(srcImage, grayImage, CV_BGR2GRAY);

//create empty images of same size as the copied images
corners1= cvCreateImage(cvGetSize(srcImage), IPL_DEPTH_32F, 1);
corners2= cvCreateImage(cvGetSize(srcImage),IPL_DEPTH_32F, 1);

cvGoodFeaturesToTrack (grayImage, corners1, corners2, corners,
&cornerCount, 0.05, 5, 0);

printf("num corners found: %d/n", cornerCount);

// draw circles at each corner location in the gray image and
// print out a list the corners
if(cornerCount>0)
{
for (i=0; i<cornerCount; i++)
{
cvCircle(srcImage, cvPoint((int)(corners[i].x), (int)(corners[i].y)), 1,
color, 2, CV_AA, 0);
}
}

cvShowImage( "image", srcImage );
cvWaitKey(0); // wait for key. The function has

cvDestroyWindow("image");
cvReleaseImage(&srcImage);
cvReleaseImage(&grayImage);
cvReleaseImage(&corners1);
cvReleaseImage(&corners2);
return 0;
}