实战 | OpenCV中更稳更快的找圆方法--EdgeDrawing使用演示(详细步骤 + 代码)

2024-10-31 08:30   重庆  

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    本文主要介绍如何在OpenCV中使用EdgeDrawing模块查找圆(详细步骤 + 代码)。


      

背景介绍

    OpenCV4.5.2开始,Contrib模块中封装了开源库ED_Lib用于查找图像中的直线、线段、椭圆和圆。Github地址:

https://github.com/CihanTopal/ED_Lib

    算法原理简介:

    边缘绘制(ED)算法是一种解决边缘检测问题的主动方法。与许多其他遵循减法方法的现有边缘检测算法相比(即在图像上应用梯度滤波器后,根据多种规则消除像素,例如 Canny 中的非极大值抑制和滞后),ED 算法通过加法策略工作,即逐一选取边缘像素,因此称为“边缘绘制”。然后我们处理这些随机形状的边缘段以提取更高级别的边缘特征,即直线、圆、椭圆等。从阈值梯度幅度中提取边缘像素的流行方法是非极大值抑制,它测试每个像素是否具有最大值沿其梯度方向的梯度响应,如果没有则消除。然而,此方法不检查相邻像素的状态,因此可能会导致低质量(在边缘连续性、平滑度、薄度、定位方面)边缘片段。ED 不是非极大值抑制,而是指向一组边缘像素,并通过最大化边缘段的总梯度响应来将它们连接起来。因此,它可以提取高质量的边缘片段,而不需要额外的滞后步骤。

    OpenCV中使用介绍文档:

https://docs.opencv.org/4.5.2/d1/d1c/classcv_1_1ximgproc_1_1EdgeDrawing.html

      

使用步骤

    EdgeDrawing类是在Contrib的ximgproc模块中,C++中使用它需要满足以下条件:

    ① OpenCV >= 4.5.2

    ② CMake编译Contrib模块

    ③ 包含edge_drawing.hpp头文件

    Python中使用需要安装opencv-python-contrib >=4.5.2

【1】Python中使用演示:

#公众号--OpenCV与AI深度学习
'''This example illustrates how to use cv.ximgproc.EdgeDrawing class.Usage: ed.py [<image_name>] image argument defaults to board.jpg'''# Python 2/3 compatibilityfrom __future__ import print_functionimport numpy as npimport cv2 as cvimport random as rngimport sysrng.seed(12345)def main():try: fn = sys.argv[1]except IndexError: fn = 'board.jpg' src = cv.imread(cv.samples.findFile(fn)) gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY) cv.imshow("source", src) ssrc = src.copy()*0 lsrc = src.copy() esrc = src.copy() ed = cv.ximgproc.createEdgeDrawing()# you can change parameters (refer the documentation to see all parameters) EDParams = cv.ximgproc_EdgeDrawing_Params() EDParams.MinPathLength = 50 # try changing this value between 5 to 1000 EDParams.PFmode = False # defaut value try to swich it to True EDParams.MinLineLength = 20 # try changing this value between 5 to 100 EDParams.NFAValidation = True # defaut value try to swich it to False ed.setParams(EDParams)# Detect edges# you should call this before detectLines() and detectEllipses() ed.detectEdges(gray) segments = ed.getSegments() lines = ed.detectLines() ellipses = ed.detectEllipses()#Draw detected edge segmentsfor i in range(len(segments)): color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)) cv.polylines(ssrc, [segments[i]], False, color, 1, cv.LINE_8) cv.imshow("detected edge segments", ssrc)#Draw detected linesif lines is not None: # Check if the lines have been found and only then iterate over these and add them to the image lines = np.uint16(np.around(lines))for i in range(len(lines)): cv.line(lsrc, (lines[i][0][0], lines[i][0][1]), (lines[i][0][2], lines[i][0][3]), (0, 0, 255), 1, cv.LINE_AA) cv.imshow("detected lines", lsrc)#Draw detected circles and ellipsesif ellipses is not None: # Check if circles and ellipses have been found and only then iterate over these and add them to the imagefor i in range(len(ellipses)): center = (int(ellipses[i][0][0]), int(ellipses[i][0][1])) axes = (int(ellipses[i][0][2])+int(ellipses[i][0][3]),int(ellipses[i][0][2])+int(ellipses[i][0][4])) angle = ellipses[i][0][5] color = (0, 0, 255)if ellipses[i][0][2] == 0: color = (0, 255, 0) cv.ellipse(esrc, center, axes, angle,0, 360, color, 2, cv.LINE_AA) cv.imshow("detected circles and ellipses", esrc) cv.waitKey(0) print('Done')if __name__ == '__main__': print(__doc__) main()    cv.destroyAllWindows()

    执行指令:ed.py [<image_name>]

    实例1: edge_drawing.py 1.png

    实例2: edge_drawing.py 2.png

    实例3: edge_drawing.py 3.png

    上述图中,绿色表示找到的椭圆,红色表示找到的圆。当然,EdgeDrawing还可以获取边缘信息和查找直线,效果如下:

【2】C++中使用演示:

//公众号--OpenCV与AI深度学习
#include <iostream>#include <opencv2/opencv.hpp>#include <opencv2/ximgproc/edge_drawing.hpp>
using namespace std;using namespace cv;using namespace ximgproc;
int main(){ Mat src = imread("./imgs/11.bmp"); if (src.empty()) { cout << "src image is empty, check again!" << endl; return -1; } //resize(src, src, Size(), 0.2, 0.2); imshow("src", src); Mat gray; cvtColor(src, gray, COLOR_BGR2GRAY);
double start = static_cast<double>(getTickCount()); //计时开始 Ptr<EdgeDrawing> ed = createEdgeDrawing(); ed->params.EdgeDetectionOperator = EdgeDrawing::PREWITT; ed->params.MinPathLength = 50; // try changing this value between 5 to 1000 ed->params.PFmode = false; //defaut value try to swich it to true ed->params.MinLineLength = 10; // try changing this value between 5 to 100 ed->params.NFAValidation = false; // defaut value try to swich it to false  ed->params.GradientThresholdValue = 20;

    实例1: 

    实例2: 

    实例3:


      

简单总结

    总体来说EdgeDrawing提供的找圆和直线的方法简单易用且效果好,简单情况下使用默认参数即可。参数调整可以参考文档自己尝试,这里挑几个常用简单说明一下。

Ptr<EdgeDrawing> ed = createEdgeDrawing();ed->params.EdgeDetectionOperator = EdgeDrawing::LSD;ed->params.MinPathLength = 50; // try changing this value between 5 to 1000ed->params.PFmode = false; //defaut value try to swich it to trueed->params.MinLineLength = 10; // try changing this value between 5 to 100ed->params.NFAValidation = true; // defaut value try to swich it to falseed->params.GradientThresholdValue = 20;

【1】算法使用的梯度算子,可选4种,默认是PREWITT,大家可以设置不同的梯度算子尝试效果。

【2】梯度阈值GradientThresholdValue,值越小,更能找到对比度低的圆。比如下面分别是梯度阈值为100和50的效果:

【3】NFAValidation:默认值为true。指示是否将NFA(错误警报数)算法用于直线和椭圆验证。设置为false时,能找到更多圆或直线。

【4】MinPathLength:最小连接像素长度处理以创建边缘段。在梯度图像中,为创建边缘段而处理的最小连接像素长度。具有高于GradientThresholdValue的值的像素将被处理,默认值为10。下面分别是下面分别是梯度值为5010的效果(值越小,更小的圆被找到):

—THE END—

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