Unexpected result after excute morphology.skeletonize

[xiaozhu1988]

Description:

in the zip file,there are two files. 1)temp_0.tif is the source file;2)temp_0_skel.tif is the result after excute method morphology.skeletonize. they are different. wish for your reply thanks

Way to reproduce:

from skimage import morphology import cv2 import matplotlib.pyplot as plt from skimage.util import invert import numpy as np file=r"D:\0Temp\jiangxiy\split\temp_0.tif" file_ex=r"D:\0Temp\jiangxiy\split\temp_0_skel.tif" imgGray = cv2.imread(file, flags=0) # flags=0 灰度图像

ret, imgBin = cv2.threshold(imgGray, 0, 255, cv2.THRESH_BINARY) # 二值化处理 imgBin[imgBin==255] = 1

skeleton01 = morphology.skeletonize(imgBin) skeleton = skeleton01.astype(np.uint8) * 255 cv2.imwrite(file_ex,skeleton)

plt.figure(figsize=(8, 6)) plt.subplot(121), plt.axis('off'), plt.title("origin") plt.imshow(imgBin, cmap='gray', vmin=0, vmax=255) plt.subplot(122), plt.title("skeleton"), plt.axis('off') plt.imshow(skeleton, cmap='gray', vmin=0, vmax=255) plt.tight_layout() plt.show()

Version information:

No response

[jni]

The result seems reasonable to me @xiaozhu1988? Why do you think it is incorrect?

[xiaozhu1988]

The result seems reasonable to me @xiaozhu1988? Why do you think it is incorrect? thanks for you replay.i have written a method with opencv,but the result is differenct.i also feel confued. the part in the red retangle is the different place.

[jni]

"different" and "incorrect" are not the same thing. You could overlay the skeleton on the object to make it clearer what the skeletonization algorithm is doing. But there are many different skeletonization algorithms with different assumptions and naturally different results. To me, all of the results shown so far seem plausible.

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[lagru]

I closing this. Please feel very welcome to reopen, in case you would like to add something or think this is still relevant. :)