出处：http://blog.csdn.net/lichengyu/article/details/8009246
《图像处理分析与机器视觉》
计算全局图像中各个像素点对子图像的距离。
| AL | AL |
| AL | P |
| AL |
Mask 1
| BR | |
| P | BR |
| BR | BR |
Mask 2
1. 将图像进行二值化，子图像值为0，背景为255；
2. 利用Mask 1从左向右，从上到下扫描，p点是当前像素点，q点是Mask 1中AL邻域中的点，D()为距离计算，包括棋盘距离、城市距离和欧式距离。F(p)为p点的像素值，计算
F(p) = min( F(p), F(q)+D(p,q) ), 其中，q属于AL.
3. 再利用Mask 2从右向左，从下向上扫描，计算
F(p) = min( F(p), F(q)+D(p,q) ), 其中，q属于BR
4. F(p) 则为距离变换后的图像。
#include "opencv2/imgproc/imgproc.hpp" #include "opencv2/highgui/highgui.hpp" #include "math.h" #include <stdio.h> using namespace cv; Mat& DistTran(Mat& I); Mat& NormImage(Mat& I); static float Round(float f) { return ( ceil(f)-f > f-floor(f) ) ? floor(f) : ceil(f); } int ChessBoardDist(int x1, int y1, int x2, int y2) { return (abs(x1-x2) > abs(y1-y2)) ? abs(x1-x2) : abs(y1-y2); } int CityBlockDist(int x1, int y1, int x2, int y2) { return ( abs(x1-x2) + abs(y1-y2) ); } float EuclideanDist(int x1, int y1, int x2, int y2) { return sqrt( (float)((x1-x2)*(x1-x2) + (y1-y2)*(y1-y2)) ); } int MyMin(int x, int y) { return (x < y) ? x : y; } float MyMin(float x, float y) { return (x < y) ? x : y; } /** * @function main */ int main( int argc, char** argv ) { char* imageName = "test_wushuang.bmp"; Mat image; image = imread(imageName,1); if(!image.data) { printf("No image data\n"); } Mat gray_image; cvtColor( image, gray_image, CV_RGB2GRAY ); DistTran( gray_image ); NormImage( gray_image ); imwrite("EuclideanDist_wushuang.bmp", gray_image); namedWindow( imageName, CV_WINDOW_AUTOSIZE ); namedWindow( "Gray image", CV_WINDOW_AUTOSIZE ); imshow( imageName, image ); imshow( "Gray image", gray_image ); waitKey(0); return 0; } Mat& DistTran(Mat& I) { // accept only char type matrices CV_Assert(I.depth() != sizeof(uchar)); int channels = I.channels(); int nRows = I.rows * channels; int nCols = I.cols; //if (I.isContinuous()) //{ // nCols *= nRows; // nRows = 1; //} int i,j; uchar* p; uchar* q; //int min = 0; //int dis = 0; float fMin = 0.0; float fDis = 0.0; // pass throuth from top to bottom, left to right for( i = 1; i < nRows-1; ++i) { p = I.ptr<uchar>(i); for ( j = 1; j < nCols; ++j) { /*q = I.ptr<uchar>(i-1); dis = CityBlockDist(i, j, i-1, j-1); min = MyMin( p[j], dis+q[j-1] ); dis = CityBlockDist(i, j, i-1, j); min = MyMin( min, dis+q[j] ); q = I.ptr<uchar>(i); dis = CityBlockDist(i, j, i, j-1); min = MyMin( min, dis+q[j-1] ); q = I.ptr<uchar>(i+1); dis = CityBlockDist(i, j, i+1, j-1); min = MyMin( min, dis+q[j-1] ); p[j] = min;*/ q = I.ptr<uchar>(i-1); fDis = EuclideanDist(i, j, i-1, j-1); fMin = MyMin( (float)p[j], fDis+q[j-1] ); fDis = EuclideanDist(i, j, i-1, j); fMin = MyMin( fMin, fDis+q[j] ); q = I.ptr<uchar>(i); fDis = EuclideanDist(i, j, i, j-1); fMin = MyMin( fMin, fDis+q[j-1] ); q = I.ptr<uchar>(i+1); fDis = EuclideanDist(i, j, i+1, j-1); fMin = MyMin( fMin, fDis+q[j-1] ); p[j] = (uchar)Round(fMin); } } // pass throuth from bottom to top, right to left for( i = nRows-2; i > 0; i-- ) { p = I.ptr<uchar>(i); for( j = nCols-1; j >= 0; j-- ) { /*q = I.ptr<uchar>(i+1); dis = CityBlockDist(i, j, i+1, j); min = MyMin( p[j], dis+q[j] ); dis = CityBlockDist(i, j, i+1, j+1); min = MyMin( min, dis+q[j+1] ); q = I.ptr<uchar>(i); dis = CityBlockDist(i, j, i, j+1); min = MyMin( min, dis+q[j+1] ); q = I.ptr<uchar>(i-1); dis = CityBlockDist(i, j, i-1, j+1); min = MyMin( min, dis+q[j+1] ); p[j] = min;*/ q = I.ptr<uchar>(i+1); fDis = EuclideanDist(i, j, i+1, j); fMin = MyMin( (float)p[j], fDis+q[j] ); fDis = EuclideanDist(i, j, i+1, j+1); fMin = MyMin( fMin, fDis+q[j+1] ); q = I.ptr<uchar>(i); fDis = EuclideanDist(i, j, i, j+1); fMin = MyMin( fMin, fDis+q[j+1] ); q = I.ptr<uchar>(i-1); fDis = EuclideanDist(i, j, i-1, j+1); fMin = MyMin( fMin, fDis+q[j+1] ); p[j] = (uchar)Round(fMin); } } return I; } Mat& NormImage(Mat& I) { // accept only char type matrices CV_Assert(I.depth() != sizeof(uchar)); int channels = I.channels(); int nRows = I.rows * channels; int nCols = I.cols; //if (I.isContinuous()) //{ // nCols *= nRows; // nRows = 1; //} int i,j; uchar* p; int min = 256; int max = -1; // Do not count the outer boundary for( i = 1; i < nRows-1; ++i) { p = I.ptr<uchar>(i); for ( j = 1; j < nCols-1; ++j) { if( min > p[j] ) min = p[j]; if( max < p[j] ) max = p[j]; } } for( i = 1; i < nRows-1; ++i) { p = I.ptr<uchar>(i); for ( j = 1; j < nCols-1; ++j) { p[j] = (p[j] - min) * 255 / (max - min); } } return I; }
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