Python cv2 HoughLines网格线检测

时间:2013-09-27 15:03:48

标签: python opencv image-processing numpy hough-transform

我在图像中有一个简单的网格,我正在尝试确定网格大小,例如6x6,12x12等。使用Python和cv2。

enter image description here

我正在使用上面的3x3网格测试它,我计划通过在图像中检测它们来计算有多少垂直/水平线来确定网格大小:

import cv2
import numpy as np

im = cv2.imread('photo2.JPG')
gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)

imgSplit = cv2.split(im)
flag,b = cv2.threshold(imgSplit[2],0,255,cv2.THRESH_OTSU) 

element = cv2.getStructuringElement(cv2.MORPH_CROSS,(1,1))
cv2.erode(b,element)

edges = cv2.Canny(b,150,200,3,5)

while(True):

    img = im.copy()

    lines = cv2.HoughLinesP(edges,1,np.pi/2,2, minLineLength = 620, maxLineGap = 100)[0]

    for x1,y1,x2,y2 in lines:        
        cv2.line(img,(x1,y1),(x2,y2),(0,255,0),1)

    cv2.imshow('houghlines',img)

    if k == 27:
        break

cv2.destroyAllWindows()

我的代码会检测到这些行,如下所示,但是我的图像中每行检测到多行:

enter image description here

(图像中的每一行都有两条1px绿线)

我不能简单地将行数除以2,因为(取决于网格大小)有时只绘制一行。

如何更准确地检测并绘制原始图像中检测到的每一行的单行?

我调整了阈值设置,将图像缩小为黑白,但仍然有多行。我认为这是因为canny边缘检测?

3 个答案:

答案 0 :(得分:10)

我最终遍历这些线并删除彼此相差10px的线:

lines = cv2.HoughLinesP(edges,1,np.pi/180,275, minLineLength = 600, maxLineGap = 100)[0].tolist()

for x1,y1,x2,y2 in lines:
    for index, (x3,y3,x4,y4) in enumerate(lines):

        if y1==y2 and y3==y4: # Horizontal Lines
            diff = abs(y1-y3)
        elif x1==x2 and x3==x4: # Vertical Lines
            diff = abs(x1-x3)
        else:
            diff = 0

        if diff < 10 and diff is not 0:
            del lines[index]

gridsize = (len(lines) - 2) / 2

答案 1 :(得分:1)

你可以扩大图像 kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (2, 2)) dilated = cv2.dilate(edges, kernel, iterations=5) 然后应用cv2.HoughLinesP

答案 2 :(得分:1)

Hough函数有没有这样的参数吗? MaxLineGap?因此,如果您的线条厚度为2px,则将该参数设置为3?它不起作用吗?