墙上裂纹检测——阈值处理（全局、局部）

Python版本是Python3.7.3，OpenCV版本OpenCV3.4.1，开发环境为PyCharm
原照片

import cv2 as cv
import numpy as np
#全局阈值
def threshold_demo(image):
    gray = cv.cvtColor(image, cv.COLOR_RGB2GRAY)  #把输入图像灰度化
    #直接阈值化是对输入的单通道矩阵逐像素进行阈值分割。
    ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_TRIANGLE)
    print("threshold value %s"%ret)
    cv.namedWindow("binary0", cv.WINDOW_NORMAL)
    cv.imshow("binary0", binary)
    
#局部阈值
def local_threshold(image):
    gray = cv.cvtColor(image, cv.COLOR_RGB2GRAY)  #把输入图像灰度化
    #自适应阈值化能够根据图像不同区域亮度分布，改变阈值
    binary =  cv.adaptiveThreshold(gray, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C,cv.THRESH_BINARY, 35, 0)
    cv.namedWindow("binary1", cv.WINDOW_NORMAL)
    cv.imshow("binary1", binary)

#自适应阈值
def custom_threshold(image):
    gray = cv.cvtColor(image, cv.COLOR_RGB2GRAY)  #把输入图像灰度化
    h, w =gray.shape[:2]
    m = np.reshape(gray, [1,w*h])
    mean = m.sum()/(w*h)
    print("mean:",mean)
    ret, binary =  cv.threshold(gray, mean, 255, cv.THRESH_BINARY)
    cv.namedWindow("binary2", cv.WINDOW_NORMAL)
    cv.imshow("binary2", binary)

src = cv.imread("067.jpg")
cv.namedWindow('input_image', cv.WINDOW_NORMAL) 
cv.imshow('input_image', src)
threshold_demo(src)
local_threshold(src)
custom_threshold(src)
cv.waitKey(0)
cv.destroyAllWindows()

运行程序，显示结果

全局阈值

局部阈值

自适应阈值