OpenCV Python threshold阈值功能

cv2.threshhold():当像素值高于阈值时，我们给这个像素赋予一个新值，否则给他赋予另一个值

这个函数的第一个参数就是原图像，一般是灰度图（貌似非灰度图也可以）。第二个参数就是用来对像素值进行分类的阈值。第三个参数就是当像素值高于阈值时应该被赋予的新像素值。

OpenCV提供了多种不同的阈值方法，这是第四个参数。这些方法包括：

1. 1. 
      
2. cv2.THRESH_BINARY           超过阈值部分取maxval（最大值），否则取0
3. cv2.THRESH_BINARY_INV    THRESH_BINARY的反转
4. cv2.THRESH_TRUNC            大于阈值部分设为阈值，否则不变
5. cv2.THRESH_TOZERO          大于阈值部分不改变，否则设为0
6. cv2.THRESH_TOZERO_INV  THRESH_TOZERO的反转
   1. 
      

示例代码：

import  cv2
from matplotlib import pyplot as plt

img = cv2.imread('00.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]
#pyplot的绘图方法
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()