OpenCV:圖像的普通二值化

首先我們來看看圖像二值化的過程，opencv一共有好幾種不同的二值化算法可以使用，一般來說圖像的像素，亮度等條件如果超過了某個或者低於了某個閾值，就會恆等於某個值，可以用於某些物體輪廓的監測：

導包：

import numpy as np
import cv2
import matplotlib.pyplot as plt
def 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

讀入圖像：

image=imread('123.jpg')
show(image)
gray=cv2.cvtColor(image,cv2.COLOR_RGB2GRAY)
plt.imshow(gray,'gray')#這里需要加一個參數之后才可以顯示灰度圖
plt.axis('off')
plt.show()

進行二值化的參數設定：

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)

進行二值化：

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()