用python写二值图像骨架提取代码

以下是一个基于 Python 和 OpenCV 库实现的二值图像骨架提取代码：

import cv2

# 实现 Zhang-Suen 骨架提取算法
def thinningIteration(img, iter):
    marker = cv2.bitwise_and(img, cv2.bitwise_not(cv2.erode(img, None)))

    while cv2.countNonZero(marker) > 0:
        temp = cv2.bitwise_and(cv2.bitwise_not(cv2.dilate(marker, None)), img)
        img = cv2.bitwise_or(img, temp)
        marker = cv2.bitwise_and(img, cv2.bitwise_not(cv2.erode(img, None)))

    return img

# 实现 Zhang-Suen 骨架提取算法
def thinning(img):
    img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)[1]

    prev = np.zeros(img.shape, np.uint8)
    diff = None

    while True:
        img = thinningIteration(img, 0)
        img = thinningIteration(img, 1)
        diff = cv2.absdiff(img, prev)
        prev = img.copy()
        if cv2.countNonZero(diff) == 0:
            break

    return img

if __name__ == '__main__':
    img = cv2.imread('test.png', cv2.IMREAD_GRAYSCALE)
    skeleton = thinning(img)
    cv2.imshow('Skeleton', skeleton)
    cv2.waitKey(0)

其中，`thinning()` 函数实现 Zhang-Suen 骨架提取算法，`thinningIteration()` 函数实现骨架提取的迭代过程。

调用示例：

1. 读取二值图像 `test.png`：

img = cv2.imread('test.png', cv2.IMREAD_GRAYSCALE)

2. 进行骨架提取：

skeleton = thinning(img)

3. 显示结果：

cv2.imshow('Skeleton', skeleton)
cv2.waitKey(0)