論文地址：A fast parallel algorithm for thinning digital patterns
代碼：
def thinImage(src, maxIterations=-1):
assert len(src.shape) == 2, 'please binarify pictures'
img_height, img_width = src.shape
dst = src.copy()
count = 0
while True:
count +=1
if maxIterations != -1 and count > maxIterations:
break
mFlag = []
for i in range(img_height):
for j in range(img_width):
p1 = dst[i, j]
if p1 != 1:
continue
p4 = 0 if j == img_width-1 else dst[i, j+1]
p8 = 0 if j == 0 else dst[i, j-1]
p2 = 0 if i == 0 else dst[i-1, j]
p3 = 0 if i == 0 or j == img_width-1 else dst[i-1, j+1]
p9 = 0 if i == 0 or j == 0 else dst[i-1, j-1]
p6 = 0 if i == img_height-1 else dst[i+1, j]
p5 = 0 if i == img_height-1 or j == img_width-1 else dst[i+1, j+1]
p7 = 0 if i == img_height-1 or j == 0 else dst[i+1, j-1]
if p2+p3+p4+p5+p6+p7+p8+p9>=2 and p2+p3+p4+p5+p6+p7+p8+p9<=6:
ap = 0
if p2 == 0 and p3 ==1:
ap+=1
if p3 == 0 and p4 == 1:
ap+=1
if p4 ==0 and p5 == 1:
ap+=1
if p5 == 0 and p6 == 1:
ap+=1
if p6 == 0 and p7 == 1:
ap+=1
if p7 == 0 and p8 == 1:
ap+=1
if p8 == 0 and p9 == 1:
ap+=1
if p9 == 0 and p2 == 1:
ap+=1
if ap == 1 and p2*p4*p6 == 0 and p4*p6*p8 == 0:
mFlag.append([i, j])
for flag in mFlag:
dst[flag[0], flag[1]] = 0
if len(mFlag) == 0:
break
else:
mFlag.clear()
for i in range(img_height):
for j in range(img_width):
p1 = dst[i, j]
if p1 != 1:
continue
p4 = 0 if j == img_width-1 else dst[i, j+1]
p8 = 0 if j == 0 else dst[i, j-1]
p2 = 0 if i == 0 else dst[i-1, j]
p3 = 0 if i == 0 or j == img_width-1 else dst[i-1, j+1]
p9 = 0 if i == 0 or j == 0 else dst[i-1, j-1]
p6 = 0 if i == img_height-1 else dst[i+1, j]
p5 = 0 if i == img_height-1 or j == img_width-1 else dst[i+1, j+1]
p7 = 0 if i == img_height-1 or j == 0 else dst[i+1, j-1]
if p2+p3+p4+p5+p6+p7+p8+p9>=2 and p2+p3+p4+p5+p6+p7+p8+p9<=6:
ap = 0
if p2 == 0 and p3 ==1:
ap+=1
if p3 == 0 and p4 == 1:
ap+=1
if p4 ==0 and p5 == 1:
ap+=1
if p5 == 0 and p6 == 1:
ap+=1
if p6 == 0 and p7 == 1:
ap+=1
if p7 == 0 and p8 == 1:
ap+=1
if p8 == 0 and p9 == 1:
ap+=1
if p9 == 0 and p2 == 1:
ap+=1
if ap == 1 and p2*p4*p8 == 0 and p2*p6*p8 == 0:
mFlag.append([i, j])
for flag in mFlag:
dst[flag[0], flag[1]] = 0
if len(mFlag) == 0:
break
else:
mFlag.clear()
return dst
if __name__ == '__main__':
startTime = time.time()
files = ['C:/Users/tellw/Desktop/toSkeleton.png', 'C:/Users/tellw/Desktop/1.png']
for file in files:
img = cv2.imread(file, 0)
_, img = cv2.threshold(img, 128, 1, cv2.THRESH_BINARY)
img = thinImage(img)
img[img==1] = 255
cv2.imshow('%s after process'%file, img)
print('running %f s'%(time.time()-startTime))
cv2.waitKey()
運行結果：
參考鏈接：
圖像細化 A fast parallel algorithm for thinning digital patterns
基於zhang 的骨架提取