以代码为基础的opencv-python学习 图像二值化

Posted 2021-03-03 august2019

import cv2
import numpy as np

#此方法可以将彩色图根据一定的阈值转换为黑白图。其中阈值用于划分图片的黑白(局部方法)
def threshold_deom(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    ret, binary = cv2.threshold(gray, 127,255,cv2.THRESH_BINARY)#可将图像中的颜色转为0或1，即黑和白。其中127表示阈值，大于127的是白色，小于127的是黑色。当然这个也取决于cv2.THRESH_XX函数    
    ret, binary = cv2.threshold(gray, 0,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)#不自定义，而是使用cv2函数
    print("threshold value=",ret)
    cv2.imshow("binary",binary)

#自适应方法，效果更好
def local_threshold(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    dst = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,25,10)
    cv2.imshow("binary",dst)

src = cv2.imread("woman.jpg")
cv2.namedWindow("input image",cv2.WINDOW_AUTOSIZE)
cv2.imshow(‘input image‘,src)
threshold_deom(src)
cv2.waitKey(0)
cv2.destroyAllWindows()