图像阀值处理

cv2.threshold（）

cv2.THRESH_BINARY   #二值化处理，低于阈值的像素点灰度值置为0；高于阈值的值置为参数3
cv2.THRESH_BINARY_INV   #大于阈值的像素点灰度值置为0；小于阈值置为参数3
cv2.THRESH_TRUNC     #小于阈值的像素点灰度值不变，大于阈值的像素点置为该阈值
cv2.THRESH_TOZERO   #小于阈值的像素点灰度值不变，大于阈值的像素点置为0,其中参数3任取
cv2.THRESH_TOZERO_INV   大于阈值的像素点灰度值不变，小于阈值的像素点置为0,其中参数3任取

img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)   #转为灰度图

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

>>> 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 xrange(6):
        plt.subplot(2,3,i+1),plt.imshow(images[i],'gray')
        plt.title(titles[i])
        plt.xticks([]),plt.yticks([])