图像处理（二）距离变换

距离变换就是将距离变换为灰度，距离是矩阵的秩中任一点与秩外的距离的最小值，效果图:
代码如下：

import numpy as np
import cv2

image = cv2.imread(‘test.jpg’)
image = cv2.resize(image,(100,100))
image = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
hight,width = image.shape
image = cv2.threshold(image,127,255,cv2.THRESH_BINARY)

image = image[1]
#print(image)
img = np.zeros((hight,width))
dis_0 = []
dis_1 = []

for i in range(hight):
for j in range(width):
if image[i,j]==0:
dis_0.append((i,j))
else:
dis_1.append((i,j))

for data_1 in dis_1:
min_ = 1000
for data_0 in dis_0:
dis = pow(pow(data_1[0]-data_0[0],2)+pow(data_1[1]-data_0[1],2),.5)
if dis<min_:
min_ = dis

img[data_1[0],data_1[1]] = min_

img = img.astype(np.uint8)
cv2.imshow(‘test’,5*img)
cv2.waitKey(0)
cv2.destroyWindows()