opencv使用cv2.threshold()实现图像阈值处理

首先介绍一下函数：ret, dst = cv2.threshold(src, thresh, maxval, type)的各参数含义

1. src： 输入图，只能输入单通道图像，通常来说为灰度图
2. thresh： 阈值
3. maxval： 当像素值超过了阈值或者小于阈值，根据type所决定的要赋予像素点的值

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

4. dst： 输出图
5. ret： 阈值
   下面通过一个示例来看一下具体怎么使用它来进行图像阈值处理以及处理之后的效果

img=cv2.imread('cat.jpg')
img_gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret, thresh1 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY_INV)
ret, thresh3 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TRUNC)
ret, thresh4 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TOZERO)
ret, thresh5 = cv2.threshold(img_gray, 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()