利用canny和hough变换检测图像是否像素化

Question

我在网上阅读，发现可以根据使用边缘检测器检测到的线数，然后应用Hough变换来判断图像是否像素化<我试过那种方法，但霍夫变换似乎无法正确检测线条，我不明白为什么它不能正常工作
以下是一些可供参考的结果图像：canny边缘检测结果

以及霍夫变换的结果

如何改进测线检测
我使用的代码基于一些在线教程：

img = cv2.imread(image_path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

high_thresh, thresh_im = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
lowThresh = 0.5*high_thresh
edges = cv2.Canny(img, lowThresh, high_thresh)

minLineLength = 200
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)

cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Answer 1

edges = cv2.Canny(gray,50,150,apertureSize = 3)
minLineLength = 200
maxLineGap = 10
lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength,maxLineGap)
# edited this line
for line in lines:
    x1,y1,x2,y2 = line[0]
    cv2.line(image,(x1,y1),(x2,y2),(0,255,0),2)