如何在 openCV python 中使用 HoughLines 变换准确检测线条？

Question

我在 python 和 opencv 方面都是新手，我在检测下图中的线条时遇到了问题，其中有条带铺在地上的黑线：

我使用了以下代码：

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

但无法准确检测线条，仅在从底部开始的第一个黑色条带上绘制一条绿线，甚至没有覆盖整条线，
还有，
请建议一种获取每行的 y 坐标的方法。

Answer 1

桑吉，

下面显示了一个修改后的代码，它检测的不是一条霍夫线，而是多条霍夫线。我改进了如何循环遍历线数组的方式，以便您获得更多的线段。

您可以进一步调整参数，但是，我认为您的另一个 post 中的等高线方法很可能是解决您的任务的更好方法，如下所示：

import numpy as np
import cv2

img = cv2.imread('lines.jpg')

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
print img.shape[1]
print img.shape
minLineLength=img.shape[1]-300
lines = cv2.HoughLinesP(image=edges,rho=0.02,theta=np.pi/500, threshold=10,lines=np.array([]), minLineLength=minLineLength,maxLineGap=100)

a,b,c = lines.shape
for i in range(a):
    cv2.line(img, (lines[i][0][0], lines[i][0][1]), (lines[i][0][2], lines[i][0][3]), (0, 0, 255), 3, cv2.LINE_AA)


cv2.imshow('edges', edges)
cv2.imshow('result', img)

cv2.waitKey(0)
cv2.destroyAllWindows()

Answer 2

我试着在一个image.So中提取水平和垂直线我们可以使用形态学操作this.It这将是最好的problem.Try它。

Mat img = imread(argv[1]);

if(!src.data)
    cerr << "Problem loading image!!!" << endl;

imshow("img .jpg", img);

cvtColor(img, gray, CV_BGR2GRAY);
imshow("gray", gray);


Mat binary_image;
adaptiveThreshold(gray, binary_image, 255, CV_ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 15, -2);
imshow("binary.jpg", binary_image);

// Create the images that will use to extract the horizontal and vertical lines
Mat horizontal = binary_image.clone();
Mat vertical = binary_image.clone();

int horizontalsize = horizontal.cols / 30;

Mat horizontalStructure = getStructuringElement(MORPH_RECT, Size(horizontalsize,1));


erode(horizontal, horizontal, horizontalStructure, Point(-1, -1));
dilate(horizontal, horizontal, horizontalStructure, Point(-1, -1));
imshow("horizontal", horizontal);

int verticalsize = vertical.rows / 30;

Mat verticalStructure = getStructuringElement(MORPH_RECT, Size( 1,verticalsize));

erode(vertical, vertical, verticalStructure, Point(-1, -1));
dilate(vertical, vertical, verticalStructure, Point(-1, -1));

imshow("vertical", vertical);

bitwise_not(vertical, vertical);
imshow("vertical_bit", vertical);


Mat edges;
adaptiveThreshold(vertical, edges, 255, CV_ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 3, -2);
imshow("edges", edges);

Mat kernel = Mat::ones(2, 2, CV_8UC1);
dilate(edges, edges, kernel);
imshow("dilate", edges);

Mat smooth;
vertical.copyTo(smooth);

blur(smooth, smooth, Size(2, 2));

smooth.copyTo(vertical, edges);

imshow("smooth", vertical);
waitKey(0);
return 0;

如何在 openCV python 中使用 HoughLines 变换准确检测线条？

How to detect lines accurately using HoughLines transform in openCV python?

python

numpy

hough-transform

opencv3.0