How to detect lines accurately using HoughLines transform in openCV python?
Question: I am a newbie in both `python` and **`opencv`** and I am facing a problem in
detecting lines in the following image, which has strips of black lines laid
on the ground:

[![enter image description
here](http://i.stack.imgur.com/aMHlL.jpg)](http://i.stack.imgur.com/aMHlL.jpg)

I used the following code:

    
    
    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)
    

but it is unable to detect the lines accurately and only draws a green line on
the first black strip from the bottom which does not even cover the entire
line,  
also,  
please suggest a way of obtaining the **`y`** cordinates of each line.


Answer: Sanj,

a modified code which detects not one but many Hough lines is shown below. I
have improved the way how to loop through the lines array so that you get many
more line segments.

You can further tune the parameters, however, I think that the contour
approach in your other post will most likely be the better approach to solve
your task, as shown there: [How to detect horizontal lines in an image and
obtain its y-coordinates using python and
opencv?](http://stackoverflow.com/questions/36210615/how-to-detect-horizontal-
lines-in-an-image-and-obtain-its-y-coordinates-using-py)

    
    
    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()
    

