python使用cv2实现Zhang-Suen算法

使用Python的OpenCV库实现Zhang-Suen算法的步骤如下：

1. 导入所需的库

import cv2
import numpy as np

2. 读取图像并将其转换为二值图像

img = cv2.imread('image.jpg', 0)
ret, img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)

3. 定义Zhang-Suen算法的两个子算法函数

def sub_iteration(img, num):
    rows, cols = img.shape
    for i in range(rows):
        for j in range(cols):
            if img[i,j] == 0:
                continue
            neighbors = img[max(i-1,0):min(i+2,rows),max(j-1,0):min(j+2,cols)]
            if np.sum(neighbors==255) < num:
                img[i,j] = 255

def zhang_suen_iteration(img):
    rows, cols = img.shape
    img_copy = img.copy()
    sub_iteration(img_copy, 2)
    sub_iteration(img_copy, 1)
    return img_copy

其中，`sub_iteration`函数实现了Zhang-Suen算法的子算法，用于对图像进行单次迭代；`zhang_suen_iteration`函数则实现了整个算法的迭代过程。

4. 循环迭代直到图像无法再细化为止

while True:
    last_img = img.copy()
    img = zhang_suen_iteration(img)
    if np.all(img == last_img):
        break

5. 显示结果并保存图像

cv2.imshow('result', img)
cv2.imwrite('result.jpg', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

完整代码如下：

import cv2
import numpy as np

def sub_iteration(img, num):
    rows, cols = img.shape
    for i in range(rows):
        for j in range(cols):
            if img[i,j] == 0:
                continue
            neighbors = img[max(i-1,0):min(i+2,rows),max(j-1,0):min(j+2,cols)]
            if np.sum(neighbors==255) < num:
                img[i,j] = 255

def zhang_suen_iteration(img):
    rows, cols = img.shape
    img_copy = img.copy()
    sub_iteration(img_copy, 2)
    sub_iteration(img_copy, 1)
    return img_copy

img = cv2.imread('image.jpg', 0)
ret, img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)

while True:
    last_img = img.copy()
    img = zhang_suen_iteration(img)
    if np.all(img == last_img):
        break

cv2.imshow('result', img)
cv2.imwrite('result.jpg', img)
cv2.waitKey(0)
cv2.destroyAllWindows()