python – Hough线变换以在图像中查找多边形

我想在下面的图像中找到所有多边形(包括填充的多边形).目前,我正在尝试使用Hough Transform来完成此任务,但它没有检测到图像中的所有行.此外,由于线条的宽度,它每行计算两次.有没有办法对图像应用一些滤镜以使Hough变换表现更好,或者是否有完全不同的方法来找到我缺少的多边形？谢谢！

这是我正在处理的图片,

我的代码如下.

import cv2
import numpy as np

img = cv2.imread('test.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
minLineLength = 100
maxLineGap = 10
lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength,maxLineGap)
for num in range (0, len(lines)):
    for x1,y1,x2,y2 in lines[num]:
        cv2.line(img,(x1,y1),(x2,y2),(0,255,0),2)

cv2.imwrite('houghlines.jpg',img)

解决方法:

我认为使用findContours更容易解决这个问题.

以下是解决方案,我写下评论,如果您有任何疑问,请询问.

void detect_by_contour()
{
    //Following comments are written for non c++ programmers
    auto img = cv::imread("../forum_quest/data/yd8pA.png");
    if(img.empty()){
        throw std::runtime_error("cannot open image");
    }

    cv::Mat gray_img;
    cv::cvtColor(img, gray_img, CV_BGR2GRAY);
    cv::Mat thin_img;
    //make your lines as thin as possible
    morphology_skeleton(gray_img, thin_img);

    std::vector<std::vector<cv::Point>> contours;
    cv::findContours(thin_img, contours, cv::RETR_EXTERNAL,
                     cv::CHAIN_APPROX_SIMPLE);
    //remove contour if the area less than 100
    auto it = std::remove_if(std::begin(contours), std::end(contours),
                   [](std::vector<cv::Point> const &a)
    {
        return cv::boundingRect(a).area() < 100;
    });
    //remove_if move unwanted elements to the backyard of the containers
    //you need to call the erase function of the containers to remove
    //unwanted elements
    contours.erase(it, std::end(contours));

    //contour_analyzer is a class used to print out statistic info
    //of the contour
    ocv::contour_analyzer analyzer;
    //print_contour_attribute_name print out the attribute names
    //of the contours as following
    //CArea   |   BArea   | Perimeter |   Aspect  |   Extent  |  Solidity |  PolySize
    ocv::print_contour_attribute_name(std::cout);
    for(size_t i = 0; i != contours.size(); ++i){
        cv::drawContours(img, contours, static_cast<int>(i), {0,255,0}, 2);        
        std::cout<<analyzer.analyze(contours[i], 0.1);
        cv::imshow("img", img);
        cv::waitKey();
    }
    cv::imwrite("polygon.jpg", img);
}

如果你运行程序(我从github使用opencv3克隆).你会发现有5个轮廓

他们的属性是

您可以尝试通过这些属性确定多边形的类型.

detect_by_contour和morphology_skeleton的代码位于forum_quest.
ocv :: contour_analyzer analyzer和ocv :: contour_analyzer的代码位于ocv_libs.

标签：python,opencv,computer-vision,canny-operator,hough-transform
来源： https://codeday.me/bug/20190708/1400073.html