原标题:OpenCV:图像的普通二值化
原文来自:博客园 原文链接:https://www.cnblogs.com/geeksongs/p/11132606.html
首先我们来看看图像二值化的过程,opencv一共有好几种不同的二值化算法可以使用,一般来说图像的像素,亮度等条件如果超过了某个或者低于了某个阈值,就会恒等于某个值,可以用于某些物体轮廓的监测:
导包:
import numpy as npimport cv2import matplotlib.pyplot as pltdef show(image):
plt.imshow(image)
plt.axis('off')
plt.show()def imread(image):
image=cv2.imread(image)
image=cv2.cvtColor(image,cv2.COLOR_BGR2RGB) return image
读入图像:
image=imread('123.jpg')
show(image)
gray=cv2.cvtColor(image,cv2.COLOR_RGB2GRAY)
plt.imshow(gray,'gray')#这里需要加一个参数之后才可以显示灰度图plt.axis('off')
plt.show()
进行二值化的参数设定:
ret1,thresh1 = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
ret2,thresh2 = cv2.threshold(gray,127,255,cv2.THRESH_BINARY_INV)
ret3,thresh3 = cv2.threshold(gray,127,255,cv2.THRESH_TRUNC)
ret4,thresh4 = cv2.threshold(gray,127,255,cv2.THRESH_TOZERO)
ret5,thresh5 = cv2.threshold(gray,127,255,cv2.THRESH_TOZERO_INV)
进行二值化:
titles = ['original','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
images = [gray, thresh1, thresh2, thresh3, thresh4, thresh5]
plt.figure(figsize=(15,5))for i in range(6):
plt.subplot(2,3,i+1)
plt.imshow(images[i],'gray')
plt.title(titles[i])
plt.axis('off')
plt.show()
免责声明:本文来自互联网新闻客户端自媒体,不代表本网的观点和立场。
合作及投稿邮箱:E-mail:editor@tusaishared.com