python实现opencv学习十三：图像二值化

固定阈值二值化

代码：

# -*- coding=GBK -*-
import cv2 as cv
 
 
# 固定阈值
def threshold_image(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    cv.imshow("before", gray)
 
    ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)  # 大律法,全局自适应阈值 参数0可改为任意数字但不起作用
    print("Threshold：%s" % ret)
    cv.imshow("OTSU", binary)
 
    ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_TRIANGLE)  # TRIANGLE法,，全局自适应阈值, 参数0可改为任意数字但不起作用，适用于单个波峰
    print("Threshold：%s" % ret)
    cv.imshow("TRIANGLE", binary)
 
    ret, binary = cv.threshold(gray, 150, 255, cv.THRESH_BINARY)  # 自定义阈值为150,大于150的是白色 小于的是黑色
    print("Threshold：%s" % ret)
    cv.imshow("customize", binary)
 
    ret, binary = cv.threshold(gray, 150, 255, cv.THRESH_BINARY_INV)  # 自定义阈值为150,大于150的是黑色 小于的是白色
    print("Threshold：%s" % ret)
    cv.imshow("customize_ReverseColor", binary)
 
    ret, binary = cv.threshold(gray, 150, 255, cv.THRESH_TRUNC)  # 截断 大于150的是改为150  小于150的保留
    print("Threshold：%s" % ret)
    cv.imshow("cutdown_1", binary)
 
    ret, binary = cv.threshold(gray, 150, 255, cv.THRESH_TOZERO)  # 截断 小于150的是改为150  大于150的保留
    print("Threshold：%s" % ret)
    cv.imshow("cutdown_2", binary)
 
 
src = cv.imread("fengling.jpg")
threshold_image(src)
cv.waitKey(0)
cv.destroyAllWindows()

结果：

备注：

threshold()函数参考：https://blog.csdn.net/sinat_21258931/article/details/61418681

自适应阈值二值化

代码：

# -*- coding=GBK -*-
import cv2 as cv
 
 
#自适应阈值
def local_image(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    cv.imshow("before", gray)
    binary1 = cv.adaptiveThreshold(gray, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY, 25, 10) # 均值
    cv.imshow("Partial_1", binary1)
    binary2 = cv.adaptiveThreshold(gray, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY, 25, 10) # 高斯处理
    cv.imshow("Partial_2", binary2)
 
 
src = cv.imread("fengling.jpg")
local_image(src)
cv.waitKey(0)
cv.destroyAllWindows()

结果：

备注：

adaptiveThreshold()函数：https://blog.csdn.net/laoyezha/article/details/106445437

像素平均阈值二值化

代码：

# -*- coding=GBK -*-
import cv2 as cv
import numpy as np
 
 
# 求出图像均值作为阈值来二值化
def custom_image(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    cv.imshow("before", gray)
    h, w = gray.shape[:2]
    m = np.reshape(gray, [1, w * h])  # 化为一维数组
    mean = m.sum() / (w * h)
    print("mean: ", mean)
    ret, binary = cv.threshold(gray, mean, 255, cv.THRESH_BINARY)
    cv.imshow("Binary", binary)
 
 
src = cv.imread("fengling.jpg")
custom_image(src)
cv.waitKey(0)
cv.destroyAllWindows()

结果：