python——图像细化算法之矩形中轴线提取完整代码

原图：

提取效果： 迭代225次

迭代230次  完整代码：

迭代次数200，运行次数可能需要五分钟，耐心等待

#! /usr/bin/env python3
# -*- coding:utf-8 -*-
import cv2
import copy
#原理就是使图像左右方向越来越“瘦”
def v_thin(img):

    h, w = img.shape
    i_next = 1
    for i in range(h):
        for j in range(w):
            if i_next == 0:
                i_next = 1
            else:
                i_m = int(img[i, j - 1]) + int(img[i, j]) + int(img[i, j + 1]) if 0 < j < w - 1 else 1
                if img[i, j] == 0 and i_m != 0:
                    a = [0] * 9
                    for k in range(3):
                        for l in range(3):
                            if -1 < (i - 1 + k) < h and -1 < (j - 1 + l) < w and img[i - 1 + k, j - 1 + l] == 255:
                                a[k * 3 + l] = 1
                    i_sum = a[0] * 1 + a[1] * 2 + a[2] * 4 + a[3] * 8 + a[5] * 16 + a[6] * 32 + a[7] * 64 + a[8] * 128
                    img[i, j] = l_array[i_sum] * 255
                    if l_array[i_sum] == 1:
                        i_next = 0


def xi_hua(img, num=315):#迭代次数，自行设置，决定了处理结果有多“瘦”
    for i in range(num):
        v_thin(img)

    return img


l_array = [0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,
           1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1,
           0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,
           1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1,
           1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
           1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1,
           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
           0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,
           1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1,
           0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,
           1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0,
           1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
           1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0,
           1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0,
           1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0]




def to_binary(img):

    w, h = img.shape
    i_two = copy.deepcopy(img)
    for i in range(w):
        for j in range(h):
            if img[i, j] < 200:
                i_two[i, j] = 0
            else:
                i_two[i, j] = 255

    return i_two



if __name__ == '__main__':

    image = cv2.imread("./A2-2.png", 0)#读取你自己的图
    img_binary = to_binary(image)
    #cv2.imshow("image", image)#显示原图
    #cv2.imshow("img_binary", img_binary)#显示二值图
    img_thin = xi_hua(img_binary)
    #cv2.imshow("img_thin", img_thin)#显示结果
    cv2.imwrite("thin315A2.png",img_thin)#保存结果
    #cv2.waitKey(0)

亲测可用，有问题评论区