Python中的Hough变换导致错误的偏移索引错误？

Question

我正在用Python编写一个基本的Hough变换-我相信在概念上是正确的，但是，我的结果似乎是偏移的，因此它是上下分开的，而不是连续的。我想要的应该是这样的：

但我明白了：

虽然很近，但中间似乎被严重地分开了！我确信这是由于我对rho/theta数组的索引，但是尽管我做了很多修改，我还是无法修复这个问题！如果你能解释我的错误，以及我需要改变的地方，我将不胜感激！在

我的源代码应该是完整的，并直接运行。。。在

非常感谢

大卫

来源

import numpy as np
import matplotlib.pyplot as mpl

cols, rows = [256,256]  # Set size of image 
grey_levels = 256 #Grey levels in image
testPixels = [[0 for x in range(rows)] for y in range(cols)]  # Convert to black and white
testPixels[100][100] = 255 #Set 3 pixels to white
testPixels[200][200] = 255
testPixels[150][150] = 255

rho_size = int(np.sqrt(rows**2 + cols**2)) #Max possible rho is diagonal dist.
angle_size = 360 #Test all angles

houghspace = [[0 for x in range(rho_size)] for y in range(angle_size)]  # Create hough space array

for x in range(rows):  # For each rows
    for y in range(cols):  # For each cols
        if testPixels[x][y] == 0: #Skip if not edge point
            continue
        for theta in range(angle_size):
            rho = int(x*np.cos(np.deg2rad(theta)) + y*np.sin(np.deg2rad(theta)))
            houghspace[theta][rho] = 255
houghspace = [list(a) for a in zip(*houghspace)] #Transpose to get angle on x axis

fig = mpl.figure()  # Create a figure
fig.add_subplot(1, 2, 1).set_title("Original")
mpl.imshow(np.uint8(np.dstack((testPixels,testPixels,testPixels))),cmap='Greys')
fig.add_subplot(1, 2, 2).set_title("Hough Transform")
mpl.imshow(np.uint8(np.dstack((houghspace, houghspace, houghspace))),cmap='Greys')
mpl.show()

Answer 1

当您将houghspace创建为列表列表时，您混淆了索引。请更喜欢使用numpy数组，因为这样可以使索引更加清晰。沿x轴，theta改变，而沿y轴rho改变。但是，当使用列表理解来定义houghspace时，情况正好相反。在

下面是正确的代码。注意注释以##开头

rho_size = int(np.sqrt(rows**2 + cols**2)) #Max possible rho is diagonal dist.
angle_size = 360 #Test all angles

##houghspace = [[0 for y in range(angle_size) for x in range(2*rho_size)]]  #buggy
houghspace = [[0 for x in range(angle_size)] for y in range(rho_size*2)]   #correct
## Also double the rho_size, so that both crust and trough of sinusoidal is visible

for x in range(rows):  # For each rows
    for y in range(cols):  # For each cols
        if testPixels[x][y] == 0: #Skip if not edge point
            continue
        for theta in range(angle_size):
            rho = int(x*np.cos(np.deg2rad(theta)) + y*np.sin(np.deg2rad(theta))) \
                                                  + rho_size  ## also add rho_size
            ##houghspace[theta][rho] = 255   ## buggy
            houghspace[rho][theta] += 255    # <==== indices switched & it's += 
##houghspace = [list(a) for a in zip(*houghspace)] 
##Transposing not needed now (we switched indices)

fig = mpl.figure()  # Create a figure
fig.add_subplot(1, 2, 1).set_title("Original")
mpl.imshow(np.uint8(np.dstack((testPixels,testPixels,testPixels))),cmap='Greys')
fig.add_subplot(1, 2, 2).set_title("Hough Transform")
mpl.imshow(np.uint8(np.dstack((houghspace, houghspace, houghspace))),cmap='Greys')
mpl.show()

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我得到以下情节：