Problems during Skeletonization image for extracting contours

Problems during Skeletonization image for extracting contours

You need to reverse white & black, and fill all the holes by call

cv2.dilate

first:

import numpy as npimport cv2img = cv2.imread("e_5.jpg",0)size = np.size(img)skel = np.zeros(img.shape,np.uint8)ret,img = cv2.threshold(img,127,255,0)element = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))img = 255 - imgimg = cv2.dilate(img, element, iterations=3)done = Falsewhile( not done):    eroded = cv2.erode(img,element)    temp = cv2.dilate(eroded,element)    temp = cv2.subtract(img,temp)    skel = cv2.bitwise_or(skel,temp)    img = eroded.copy()    zeros = size - cv2.countNonZero(img)    if zeros==size:        done = True

Here is the result:

But, the result is not good, because there are many gaps. The following
algorithm is better, it uses functions in

scipy.ndimage.morphology

:

import scipy.ndimage.morphology as mimport numpy as npimport cv2def skeletonize(img):    h1 = np.array([[0, 0, 0],[0, 1, 0],[1, 1, 1]])     m1 = np.array([[1, 1, 1],[0, 0, 0],[0, 0, 0]])     h2 = np.array([[0, 0, 0],[1, 1, 0],[0, 1, 0]])     m2 = np.array([[0, 1, 1],[0, 0, 1],[0, 0, 0]])        hit_list = []     miss_list = []    for k in range(4):         hit_list.append(np.rot90(h1, k))        hit_list.append(np.rot90(h2, k))        miss_list.append(np.rot90(m1, k))        miss_list.append(np.rot90(m2, k))        img = img.copy()    while True:        last = img        for hit, miss in zip(hit_list, miss_list):  hm = m.binary_hit_or_miss(img, hit, miss)  img = np.logical_and(img, np.logical_not(hm))         if np.all(img == last):   break    return imgimg = cv2.imread("e_5.jpg",0)ret,img = cv2.threshold(img,127,255,0)element = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))img = 255 - imgimg = cv2.dilate(img, element, iterations=3)skel = skeletonize(img)imshow(skel, cmap="gray", interpolation="nearest")

The result is: