(LOG)LaplacianofGuassian(DOH)DeterminantofHessian斑点检测

1. 原理

考虑一个一维信号&＃xff0c;该信号在t&＃61;1000时发生了阶跃&＃xff0c;那么如何检测这个阶跃的位置呢&＃xff1f;

图1分别用1阶高斯导数和2阶高斯导数对该信号进行卷积

(i);for(int j&＃61;0; j#if 1cornerLOG(srcImg, corner, &numCorner, height, width, minScale, maxScale, stepScale);
#elsecornerDOH(srcImg, corner, &numCorner, height, width, minScale, maxScale, stepScale);
#endifdelete[] srcImg;cv::Mat showImg;cvtColor(img, showImg, CV_GRAY2BGR);for(int i&＃61;0; i}void getLOGkernel(int halfWin, float sita, float** kernel)
{int winSize &＃61; 2*halfWin&＃43;1;float tmp1, tmp2, sumValue &＃61; 0;float powsita &＃61; sita*sita;for(int i&＃61;-halfWin; i<&＃61;halfWin; i&＃43;&＃43;){for(int j&＃61;-halfWin; j<&＃61;halfWin; j&＃43;&＃43;){tmp1 &＃61; -1*(i*i&＃43;j*j)/(2*powsita);tmp2 &＃61; exp(tmp1)*(i*i&＃43;j*j-2*powsita);//exp(tmp1)*(1&＃43;tmp1)/(-1*powsita*powsita);sumValue &＃43;&＃61; tmp2;(*kernel)[(i&＃43;halfWin)*winSize&＃43;(j&＃43;halfWin)] &＃61; tmp2;}}for(int i&＃61;0; i}void converlution(unsigned char* srcImg, int** dstImg, int height, int width, float* kernel, int kernelWin)
{for(int i&＃61;0; i&＃61;0 && m&＃61;0 && n}bool isMax(int* compImg, int compValue, _point compPoint, int kerWin, int imgWidth, bool isSameK)
{for(int i&＃61;compPoint.y-kerWin; i<&＃61;compPoint.y&＃43;kerWin; i&＃43;&＃43;){for(int j&＃61;compPoint.x-kerWin; j<&＃61;compPoint.x&＃43;kerWin; j&＃43;&＃43;){if(isSameK && i&＃61;&＃61;compPoint.y && j&＃61;&＃61;compPoint.x)continue;if(abs(compValue) <&＃61; abs(compImg[i*imgWidth&＃43;j]))return false;}}return true;
}void cornerLOG(unsigned char* srcImg, _point* corner, int* count, int height, int width, float minScale, float maxScale, int stepScale)
{int numScale &＃61; int((maxScale - minScale)/stepScale);int** scaledImg &＃61; new int*[numScale]; for(int i&＃61;0; i&＃61;MAXPOINTS){for(int m&＃61;0; m}void getDOHkernel(int halfWin, float sita, float** kernelxx, float** kernelyy, float** kernelxy)
{int winSize &＃61; 2*halfWin&＃43;1;float tmp1, tmpxx, tmpyy, tmpxy;float sumValuexx &＃61; 0, sumValueyy &＃61; 0, sumValuexy &＃61; 0;float powsita &＃61; sita*sita;for(int i&＃61;-halfWin; i<&＃61;halfWin; i&＃43;&＃43;){for(int j&＃61;-halfWin; j<&＃61;halfWin; j&＃43;&＃43;){tmp1 &＃61; -1*(i*i&＃43;j*j)/(2*powsita);tmpxx &＃61; exp(tmp1)*(j*j-powsita);tmpyy &＃61; exp(tmp1)*(i*i-powsita);tmpxy &＃61; exp(tmp1)*i*j;sumValuexx &＃43;&＃61; tmpxx;sumValueyy &＃43;&＃61; tmpyy;sumValuexy &＃43;&＃61; tmpxy;(*kernelxx)[(i&＃43;halfWin)*winSize&＃43;(j&＃43;halfWin)] &＃61; tmpxx;(*kernelyy)[(i&＃43;halfWin)*winSize&＃43;(j&＃43;halfWin)] &＃61; tmpyy;(*kernelxy)[(i&＃43;halfWin)*winSize&＃43;(j&＃43;halfWin)] &＃61; tmpxy;}}for(int i&＃61;0; i}void detValue(int** imgscale, int* imgxx, int* imgyy, int* imgxy, float scale, int height, int width)
{for(int i&＃61;0; i}void cornerDOH(unsigned char* srcImg, _point* corner, int* count, int height, int width, float minScale, float maxScale, int stepScale)
{int numScale &＃61; int((maxScale - minScale)/stepScale);int** scaledImg &＃61; new int*[numScale]; for(int i&＃61;0; i&＃61;MAXPOINTS){for(int m&＃61;0; m}




效果图&＃xff08;左LOG&＃xff0c;右DOH&＃xff09;