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<h1 style="font-size: 32px; font-weight: bold; border-bottom: 2px solid rgb(204, 204, 204); padding: 0px 4px 0px 0px; text-align: left; margin: 0px 0px 10px;">点到多边形的最短距离</h1>本章节内容是博主网上收集的，PDF原文下载地址如下：<a href="/api/system/download?file=OpenCV-Python-Tutorial-%E4%B8%AD%E6%96%87%E7%89%88.pdf" target="_blank">OpenCV-Python-Tutorial-中文版.pdf（P116 轮廓的性质）</a><a href="/upload/file/OpenCV-Python-Tutorial-%E4%B8%AD%E6%96%87%E7%89%88.pdf" target="_blank" title="PDF在线预览">PDF在线预览</a> <p style="margin-top: 0px; margin-bottom: 10px; white-space: normal; padding: 0px; list-style: none; border: 0px; overflow-wrap: break-word; word-break: break-all; line-height: 1.5em; font-family: "Helvetica Neue", Helvetica, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", "Noto Sans CJK SC", "WenQuanYi Micro Hei", Arial, sans-serif; color: rgb(51, 51, 51); box-sizing: border-box;">当前系列所有demo下载地址：<p style="margin-top: 0px; margin-bottom: 10px; white-space: normal; padding: 0px; list-style: none; border: 0px; overflow-wrap: break-word; word-break: break-all; line-height: 1.5em; font-family: "Helvetica Neue", Helvetica, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", "Noto Sans CJK SC", "WenQuanYi Micro Hei", Arial, sans-serif; color: rgb(51, 51, 51); box-sizing: border-box;"><a href="https://github.com/GaoRenBao/OpenCv4-Demo" target="_blank" style="margin: 0px; padding: 0px; list-style: none; border: 0px; color: rgb(0, 102, 0); transition-duration: 0.2s; transition-property: opacity; outline: none; opacity: 0.8;">https://github.com/GaoRenBao/OpenCv4-Demo</a><p style="margin-top: 0px; margin-bottom: 10px; text-wrap: wrap; padding: 0px; list-style: none; border: 0px; overflow-wrap: break-word; word-break: break-all; line-height: 1.5em; font-family: "Helvetica Neue", Helvetica, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", "Noto Sans CJK SC", "WenQuanYi Micro Hei", Arial, sans-serif; box-sizing: border-box; color: rgb(51, 51, 51);">不同编程语言对应的OpenCv版本以及开发环境信息如下： <table border="1" style="border-right: none; border-bottom: none; border-image: initial; border-left: 1px solid rgb(102, 102, 102); border-top: 1px solid rgb(102, 102, 102);"><tbody><tr class="firstRow"><td width="81" valign="top" style="border-color: windowtext rgb(102, 102, 102) rgb(102, 102, 102) windowtext; border-bottom-width: 1px; border-bottom-style: solid; border-right-width: 1px; border-right-style: solid; padding: 5px;">语言</td><td width="223" valign="top" style="border-color: windowtext rgb(102, 102, 102) rgb(102, 102, 102) windowtext; border-bottom-width: 1px; border-bottom-style: solid; border-right-width: 1px; border-right-style: solid; padding: 5px;">OpenCv版本</td><td width="242" valign="top" style="border-color: windowtext rgb(102, 102, 102) rgb(102, 102, 102) windowtext; border-bottom-width: 1px; border-bottom-style: solid; border-right-width: 1px; border-right-style: solid; padding: 5px;">IDE</td></tr><tr><td width="81" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">C#</td><td width="223" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">OpenCvSharp4.4.8.0.20230708</td><td width="242" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">Visual Studio 2022</td></tr><tr><td width="81" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">C++</td><td width="223" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">OpenCv-4.5.5-vc14_vc15</td><td width="242" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">Visual Studio 2022</td></tr><tr><td width="81" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">Python</td><td width="223" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">OpenCv-Python (4.6.0.66)</td><td width="242" valign="top" style="border-top: none; border-left-color: windowtext; border-bottom: 1px solid rgb(102, 102, 102); border-right: 1px solid rgb(102, 102, 102); padding: 5px;">PyCharm Community Edition 2022.1.3</td></tr></tbody></table> 当前demo演示了如何求解图像中的一个点到一个对象轮廊的最短距离。如果点在轮廊的外部，返回值为负。如果在轮廊上，返回值为0。如果在轮廊内部，返回值为正。下面我们以点（50，50）为例：dist=cv2.pointPolygonTest（cnt,（50,50），True）此函数的第三个参数是measureDist。如果设置为True，就会计算最短距离。如果是False，只会判断这个点与轮廊之间的位置关系（返回值为+1,-1,0）注意：如果你不需要知道具体距离，建议你将第三个参数为False，这样速度会提2到3倍 测试原图： <img src="/upload/image/6379848768266423382251150.png" title="lightning.png" alt="lightning.png"/>测试结果：<img src="/upload/image/6379848766922860075744359.jpg" title="QQ截图20220911100733.jpg" alt="QQ截图20220911100733.jpg"/> <strong style="margin: 0px; padding: 0px; list-style: none; border: 0px; color: rgb(51, 51, 51); font-family: "Helvetica Neue", Helvetica, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", "Noto Sans CJK SC", "WenQuanYi Micro Hei", Arial, sans-serif; ">C#版本运行代码如下：<pre class="brush:c#;toolbar:false">using OpenCvSharp; using System; namespace ConsoleApp {     internal class Program     {         static void Main(string[] args)         {             Mat srcImage = Cv2.ImRead("../../../images/lightning.png");             Mat img = new Mat();             Cv2.CvtColor(srcImage, img, ColorConversionCodes.BGR2GRAY);             Mat threshold = new Mat();             Cv2.Threshold(img, threshold, 127, 255, ThresholdTypes.Binary);             Point[][] contours = new Point[][] { };             HierarchyIndex[] hierarcy;             Cv2.FindContours(threshold, out contours, out hierarcy, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple, null);             Console.WriteLine($"contours len:{contours.Length}");             Point[] cnt = contours[0];             Point point = new Point(50, 50);             Cv2.Circle(srcImage, point, 5, new Scalar(0, 0, 255), -1);             Cv2.ImShow("srcImage", srcImage);             double dist = Cv2.PointPolygonTest(cnt, point, true);             Console.WriteLine($"距离:{dist}");             Cv2.WaitKey(0);         }     } }</pre> <strong style="margin: 0px; padding: 0px; list-style: none; border: 0px; color: rgb(51, 51, 51); font-family: "Helvetica Neue", Helvetica, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", "Noto Sans CJK SC", "WenQuanYi Micro Hei", Arial, sans-serif; ">C++版本运行代码如下：<strong style="margin: 0px; padding: 0px; list-style: none; border: 0px; color: rgb(51, 51, 51); font-family: "Helvetica Neue", Helvetica, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", "Noto Sans CJK SC", "WenQuanYi Micro Hei", Arial, sans-serif; "><pre class="brush:cpp;toolbar:false;">#include <opencv2/opencv.hpp> #include <opencv2/cvconfig.h> #include <opencv2/imgproc/imgproc.hpp> #include <opencv2/highgui/highgui.hpp>     #include <string> #include <cmath> #include <iostream> using namespace cv; using namespace std; int main() {     Mat srcImage =cv::imread("../images/lightning.png");     Mat img;     cv::cvtColor(srcImage, img, COLOR_BGR2GRAY);     Mat threshold;     cv::threshold(img, threshold, 127, 255, THRESH_BINARY); // 把黑白颜色反转     vector<vector<Point>> contours;     vector<Vec4i> hierarcy;     findContours(threshold, contours, hierarcy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));     cout << "contours len:" << contours.size() << endl;     vector<Point> cnt = contours[0];     Point point(50, 50);     cv::circle(srcImage, point, 5, Scalar(0, 0, 255), -1);     cv::imshow("srcImage", srcImage);     double dist =cv::pointPolygonTest(cnt, point, true);     cout << "距离:" << dist << endl;     cv::waitKey(0); }</pre> <strong style="margin: 0px; padding: 0px; list-style: none; border: 0px; color: rgb(51, 51, 51); font-family: "Helvetica Neue", Helvetica, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", "Noto Sans CJK SC", "WenQuanYi Micro Hei", Arial, sans-serif; ">Python版本运行代码如下：<pre class="brush:python;toolbar:false">import cv2 srcImage = cv2.imread('../images/lightning.png') img = cv2.cvtColor(srcImage, cv2.COLOR_BGR2GRAY) ret, thresh = cv2.threshold(img, 127, 255, 0) contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) print('contours len:', len(contours)) cnt = contours[0] point = (50, 50) cv2.circle(srcImage, point, 5, (0, 0, 255), -1) cv2.imshow("srcImage", srcImage) dist = cv2.pointPolygonTest(cnt, point, True) print("距离：", dist) cv2.waitKey(0) cv2.destroyAllWindows()</pre>

点到多边形的最短距离

本章节内容是博主网上收集的，PDF原文下载地址如下：

OpenCV-Python-Tutorial-中文版.pdf（P116 轮廓的性质）

PDF在线预览

当前系列所有demo下载地址：

https://github.com/GaoRenBao/OpenCv4-Demo

不同编程语言对应的OpenCv版本以及开发环境信息如下：

语言	OpenCv版本	IDE
C#	OpenCvSharp4.4.8.0.20230708	Visual Studio 2022
C++	OpenCv-4.5.5-vc14_vc15	Visual Studio 2022
Python	OpenCv-Python (4.6.0.66)	PyCharm Community Edition 2022.1.3

当前demo演示了如何求解图像中的一个点到一个对象轮廊的最短距离。如果点在轮廊的外部，返回值为负。如果在轮廊上，返回值为0。如果在轮廊内部，返回值为正。

下面我们以点（50，50）为例：

dist=cv2.pointPolygonTest（cnt,（50,50），True）

此函数的第三个参数是measureDist。如果设置为True，就会计算最短距离。如果是False，只会判断这个点与轮廊之间的位置关系（返回值为+1,-1,0）

注意：如果你不需要知道具体距离，建议你将第三个参数为False，这样速度会提2到3倍

测试原图：

测试结果：

QQ截图20220911100733.jpg

C#版本运行代码如下：

using OpenCvSharp;
using System;

namespace ConsoleApp
{
    internal class Program
    {
        static void Main(string[] args)
        {
            Mat srcImage = Cv2.ImRead("../../../images/lightning.png");
            Mat img = new Mat();
            Cv2.CvtColor(srcImage, img, ColorConversionCodes.BGR2GRAY);

            Mat threshold = new Mat();
            Cv2.Threshold(img, threshold, 127, 255, ThresholdTypes.Binary);

            Point[][] contours = new Point[][] { };
            HierarchyIndex[] hierarcy;
            Cv2.FindContours(threshold, out contours, out hierarcy, RetrievalModes.Tree, ContourApproximationModes.ApproxSimple, null);
            Console.WriteLine($"contours len:{contours.Length}");
            Point[] cnt = contours[0];

            Point point = new Point(50, 50);
            Cv2.Circle(srcImage, point, 5, new Scalar(0, 0, 255), -1);
            Cv2.ImShow("srcImage", srcImage);

            double dist = Cv2.PointPolygonTest(cnt, point, true);
            Console.WriteLine($"距离:{dist}");
            Cv2.WaitKey(0);
        }
    }
}

C++版本运行代码如下：

#include <opencv2/opencv.hpp>
#include <opencv2/cvconfig.h>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>    

#include <string>
#include <cmath>
#include <iostream>

using namespace cv;
using namespace std;

int main()
{
    Mat srcImage =cv::imread("../images/lightning.png");
    Mat img;
    cv::cvtColor(srcImage, img, COLOR_BGR2GRAY);

    Mat threshold;
    cv::threshold(img, threshold, 127, 255, THRESH_BINARY); // 把黑白颜色反转
    vector<vector<Point>> contours;
    vector<Vec4i> hierarcy;
    findContours(threshold, contours, hierarcy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));
    cout << "contours len:" << contours.size() << endl;
    vector<Point> cnt = contours[0];
    Point point(50, 50);

    cv::circle(srcImage, point, 5, Scalar(0, 0, 255), -1);
    cv::imshow("srcImage", srcImage);

    double dist =cv::pointPolygonTest(cnt, point, true);
    cout << "距离:" << dist << endl;
    cv::waitKey(0);
}

Python版本运行代码如下：

import cv2

srcImage = cv2.imread('../images/lightning.png')
img = cv2.cvtColor(srcImage, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(img, 127, 255, 0)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
print('contours len:', len(contours))
cnt = contours[0]

point = (50, 50)
cv2.circle(srcImage, point, 5, (0, 0, 255), -1)
cv2.imshow("srcImage", srcImage)

dist = cv2.pointPolygonTest(cnt, point, True)
print("距离：", dist)

cv2.waitKey(0)
cv2.destroyAllWindows()