python opencv图像阈值处理

Posted 2021-10-29 bandend

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学习函数 cv2.threshold, cv2.adaptiveThreshold等等

简单阈值：

原理很直接，如果像素值大于一个阈值，那么久将它赋值一个数，否则赋值成另外一个数。函数使用cv2.threshold
第一参数是原图像，而且这个图像应该是一个灰度图像。第二个参数用来区分像素的阈值。第三个参数是像素值大于阈值时的上限。opencv提供了不同样式的阈值并且由第四个参数决定。类型如下
cv2.THRESH_BINARY
cv2.THRESH_BINARY_INV
cv2.THRESH_TRUNC
cv2.THRESH_TOZERO
cv2.THRESH_TOZERO_INV

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import cv2
import numpy as np
from matplotlib import pyplot as plt

img = cv2.imread(‘sta.jpg‘,0)
ret,thresh1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
ret,thresh2 = cv2.threshold(img,127,255,cv2.THRESH_BINARY_INV)
ret,thresh3 = cv2.threshold(img,127,255,cv2.THRESH_TRUNC)
ret,thresh4 = cv2.threshold(img,127,255,cv2.THRESH_TOZERO)
ret,thresh5 = cv2.threshold(img,127,255,cv2.THRESH_TOZERO_INV)

titles = [‘Original Image‘,‘BINARY‘,‘BINARY_INV‘,‘TRUNC‘,‘TOZERO‘,‘TOZERO_INV‘]
images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]

for i in range(6):
    plt.subplot(2,3,i+1),plt.imshow(images[i],‘gray‘)
    plt.title(titles[i])
    plt.xticks([]),plt.yticks([])

plt.show()