检测点是否在轮廓、多边形的内部

怼烎@ 2022-03-21 05:18 215阅读 0赞

[OpenCV官网][OpenCV]

## 代码 ##

#include <opencv2/opencv.hpp>
    #include <iostream>
    
    using namespace cv;
    using namespace std;
    
    
    int main(void)
    { 
    	
        const int r=100;
        Mat src = Mat::zeros(Size(4*r, 4*r), CV_8U);
    
        vector<Point> vert(6);
        vert[0] = Point(3*r/2,static_cast<int>(1.34*r));
        vert[1] = Point(r,2*r);
        vert[2] = Point(3*r/2, static_cast<int>(2.866*r));
        vert[3] = Point(5*r/2, static_cast<int>(2.866*r));
        vert[4] = Point(3*r, 2*r);
        vert[5] = Point(5*r/2, static_cast<int>(1.34*r));
    
        for(int i=0; i<6; i++)
        { 
    	line(src, vert[i], vert[(i+1)%6], Scalar(255), 3);  //在src中创建一个六边形
        }
    
    
    
        vector<vector<Point>> contours;
        findContours(src, contours, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE); //检测六边形的轮廓
    
    	
        Mat raw_dist(src.size(), CV_32F); //存放每个点的检测结果，所以定义为CV_32F
        for(int i=0; i<src.rows; i++)
        { 
    		for(int j=0; j<src.cols; j++)
    		{ 
    	    	raw_dist.at<float>(i,j) = (float)cv::pointPolygonTest(contours[0], Point2f((float)j, (float)i), true); // 对于每个点都去检测
    		}	    
        }
    
        double minVal, maxVal;
        Point maxDistPt;
        cv::minMaxLoc(raw_dist,&minVal, &maxVal, NULL, &maxDistPt); //找到最大值和最小值，以及他们的位置
        minVal = abs(minVal);  //因为最小值肯定是负值，在contour外都是负值，所以取绝对值
        maxVal = abs(maxVal);
    
        Mat drawing = Mat::zeros(src.size(), CV_8UC3);  //将结果显示此图中
        for(int i=0; i<src.rows; i++)
        { 
    		for(int j=0; j<src.cols; j++)
    		{ 
    	    	if(raw_dist.at<float>(i,j) < 0)  //在contour外
    	    	{ 
    				drawing.at<Vec3b>(i,j)[0] = (uchar)(255-abs(raw_dist.at<float>(i,j))*255/minVal);  //，minVal已经取abs，minVal是contour外距离最远点，距离边界越远，蓝色成分越小 
    	    	}
    	    	else if(raw_dist.at<float>(i,j)>0) //在contour内
    	    	{ 
    				drawing.at<Vec3b>(i,j)[2] = (uchar)(255-raw_dist.at<float>(i,j)*255/maxVal); //距离边界越远，红色成分越小
    	    	}
    	    		else  // 边界上，白色
    	    	{ 
    				drawing.at<Vec3b>(i,j)[0] = 255 ;
    				drawing.at<Vec3b>(i,j)[1] = 255 ;
    				drawing.at<Vec3b>(i,j)[2] = 255 ;
    
    	    }
    		}
        }
    
        circle(drawing, maxDistPt, (int)maxVal, Scalar(255,255,255)); //maxDistPt 应该是contours里面最中心的位置，maxVal:到边界的距离，所以应该是一个内接圆
        imshow("source", src);
        imshow("Distance and inscribed circle", drawing);
    
        waitKey();
    
    	return 0;
    };

结果：和代码中注释分析一样，接近contour颜色深，远离边界(往内，往外两个方向)，颜色开始变浅到黑。

![在这里插入图片描述][20190130201235642.png_pic_center]

--------------------

## OpenCV API ##

1.  判断一个点是否在 polygon的内部

[double cv::pointPolygonTest ][double cv_pointPolygonTest]

( 	    InputArray  	contour,  //一组点组成contour vector<Point>
    		Point2f  	pt,           // 被检测的点
    		bool  	measureDist       // true: 内部是正数，边界是0，外部是负数,绝对值是点到最近一条边的距离； false: 检测点是否在内部、外部、边界,返回+1、-1、0
    )

[OpenCV]: https://docs.opencv.org/master/dc/d48/tutorial_point_polygon_test.html
[20190130201235642.png_pic_center]: /images/20220321/8f8436936891440e8d3bc7cf9a5acf17.png
[double cv_pointPolygonTest]: https://docs.opencv.org/master/d3/dc0/group__imgproc__shape.html#ga1a539e8db2135af2566103705d7a5722