在OpenCV中,可以很方便的计算一个像素点到轮廓的距离,计算距离的函数为:
double pointPolygonTest(InputArray contour, Point2f pt, bool measureDist)
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Parameters:
- contour – 输入参数轮廓。
- pt – 测试的点。
- measureDist – 如果为false的话,则函数计算符号,在轮廓外部在为-1,在轮廓内为1,在轮廓上,则为0。如果为ture,则计算实际的像素符号距离,在轮廓外的点像素距离为负值,在内的点,像素距离为正值。
下面的是计算一副图像中各个像素到轮廓距离的代码:
#include "opencv2/imgproc/imgproc.hpp"#include "opencv2/highgui/highgui.hpp"#include <iostream>#include <stdio.h>#include <stdlib.h>using namespace cv;using namespace std; using namespace cv;using namespace std; int main( int argc, char** argv ) {//创建一副图像const int r = 100; Mat src = Mat::zeros( Size( 4*r, 4*r ), CV_8UC1 ); //创建一个轮廓序列 vector<Point2f> vert(6); vert[0] = Point( 1.5*r, 1.34*r ); vert[1] = Point( 1*r, 2*r ); vert[2] = Point( 1.5*r, 2.866*r ); vert[3] = Point( 2.5*r, 2.866*r ); vert[4] = Point( 3*r, 2*r ); vert[5] = Point( 2.5*r, 1.34*r ); //画轮廓for( int j = 0; j < 6; j++ ) { line( src, vert[j], vert[(j+1)%6], Scalar( 255 ), 3, 8 ); } //得到轮廓 vector<vector<Point> > contours; vector<Vec4i> hierarchy; Mat src_copy = src.clone(); findContours( src_copy, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE); //计算顶点到轮廓的距离 Mat raw_dist( src.size(), CV_32FC1 ); for( int j = 0; j < src.rows; j++ ) {for( int i = 0; i < src.cols; i++ ) { raw_dist.at<float>(j,i) = pointPolygonTest( contours[0], Point2f(i,j), true ); } } double minVal; double maxVal; minMaxLoc( raw_dist, &minVal, &maxVal, 0, 0, Mat() ); minVal = abs(minVal); maxVal = abs(maxVal); //用户型化的方式显示距离 Mat drawing = Mat::zeros( src.size(), CV_8UC3 ); for( int j = 0; j < src.rows; j++ ) { for( int i = 0; i < src.cols; i++ ) {//在外部if( raw_dist.at<float>(j,i) < 0 ) { drawing.at<Vec3b>(j,i)[0] = 255 - (int) abs(raw_dist.at<float>(j,i))*255/minVal; }//在内部else if( raw_dist.at<float>(j,i) > 0 ) { drawing.at<Vec3b>(j,i)[2] = 255 - (int) raw_dist.at<float>(j,i)*255/maxVal; }else// 在边上 { drawing.at<Vec3b>(j,i)[0] = 255; drawing.at<Vec3b>(j,i)[1] = 255; drawing.at<Vec3b>(j,i)[2] = 255; } } } namedWindow( "image", CV_WINDOW_AUTOSIZE ); imshow( "image", src ); namedWindow( "Distance", CV_WINDOW_AUTOSIZE ); imshow( "Distance", drawing ); waitKey(0);return(0); }
对于轮廓外的点,越是蓝色,则距离轮廓越近,轮廓内的点,越是红色距离轮廓越近,轮廓上点距离为0,用白色表示。
程序执行后效果:
程序代码:工程FirstOpenCV30
时间: 2024-10-27 05:03:43