python实现图像边缘算法

109 阅读 0 评论 72 点赞

我是靠谱客的博主英勇路灯，这篇文章主要介绍python实现图像边缘算法，现在分享给大家，希望可以做个参考。

关于作者：
程序员：杨洪（ellende）
blog: http://blog.csdn.NET/ellende
email: yangh.personal@qq.com

转载请注明出处，引用部分网上博客，若有侵权还请作者联系与我。

1.算法原理

将当前的像素值与相邻的右部和下部的像素值进行比较，若相似，则将像素值设置为黑色，否则设置为白色。

2.判定像素值相似方法

使用欧式距离算法，将一个像素的3个色彩分量映射在三维空间中，两个像素点的距离就是三维空间的直线距离值。

3.实现代码

复制代码

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# 图像边缘算法
import cv2
import numpy as np
fn = "Z:\ellende\myworkspace\learn_library\my code\python learn\input_files\test1.jpg"
#欧式距离函数
def get_EuclideanDist(x, y):
myx = np.array(x)
myy = np.array(y)
return np.sqrt(np.sum((myx-myy)*(myx-myy)))
if __name__ == '__main__':
print 'loading %s ...' % fn
print 'working',
myimg1 = cv2.imread(fn)
w = myimg1.shape[1]
h = myimg1.shape[0]
sz1 = w
sz0 = h
#创建空白图像
myimg2 = np.zeros((sz0,sz1,3), np.uint8)
#对比产生线条
black = np.array([0,0,0])
white = np.array([255,255,255])
centercolor = np.array([125,125,125])
for y in xrange(0, sz0 - 1):
for x in xrange(0, sz1 - 1):
mydown = myimg1[y+1, x, :]
myright = myimg1[y, x+1, :]
myhere = myimg1[y,x,:]
lmyhere = myhere
lmyright = myright
lmydown = mydown
if get_EuclideanDist(lmyhere, lmydown) > 16 and get_EuclideanDist(lmyhere, lmyright) > 16:
myimg2[y,x,:] = black
elif get_EuclideanDist(lmyhere,lmydown) <= 16 and get_EuclideanDist(lmyhere, lmyright) <= 16:
myimg2[y,x,:] = white
else:
myimg2[y,x,:] = centercolor
print '.',
cv2.namedWindow('img2')
cv2.imshow('img2', myimg2)
cv2.waitKey()
cv2.destoryAllWindows()

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# 图像边缘算法
import cv2
import numpy as np
fn = "Z:\ellende\myworkspace\learn_library\my code\python learn\input_files\test1.jpg"
#欧式距离函数
def get_EuclideanDist(x, y):
myx = np.array(x)
myy = np.array(y)
return np.sqrt(np.sum((myx-myy)*(myx-myy)))
if __name__ == '__main__':
print 'loading %s ...' % fn
print 'working',
myimg1 = cv2.imread(fn)
w = myimg1.shape[1]
h = myimg1.shape[0]
sz1 = w
sz0 = h
#创建空白图像
myimg2 = np.zeros((sz0,sz1,3), np.uint8)
#对比产生线条
black = np.array([0,0,0])
white = np.array([255,255,255])
centercolor = np.array([125,125,125])
for y in xrange(0, sz0 - 1):
for x in xrange(0, sz1 - 1):
mydown = myimg1[y+1, x, :]
myright = myimg1[y, x+1, :]
myhere = myimg1[y,x,:]
lmyhere = myhere
lmyright = myright
lmydown = mydown
if get_EuclideanDist(lmyhere, lmydown) > 16 and get_EuclideanDist(lmyhere, lmyright) > 16:
myimg2[y,x,:] = black
elif get_EuclideanDist(lmyhere,lmydown) <= 16 and get_EuclideanDist(lmyhere, lmyright) <= 16:
myimg2[y,x,:] = white
else:
myimg2[y,x,:] = centercolor
print '.',
cv2.namedWindow('img2')
cv2.imshow('img2', myimg2)
cv2.waitKey()
cv2.destoryAllWindows()