python-opencv 基础系列——cv2.threshold() 函数用于图像二值化
一、cv2.threshold() 的作用将一张灰度图（单通道） 进行 二值化
1、函数详解，
def threshold(src, thresh, maxval, type, dst=None): # real signature unknown; restored from __doc__
"""（1）将灰度图变成二值化图像，也具有一定的去噪功能，去掉比较大或比较小的像素值。
threshold(src, thresh, maxval, type[, dst]) -> retval, dst #返回阈值和二值化后的图片
. @brief Applies a fixed-level threshold to each array element.（2）用固定阈值处理每个矩阵元素
. The function applies fixed-level thresholding to a multiple-channel array. The function is typically
. used to get a bi-level (binary) image out of a grayscale image ( #compare could be also used for
. this purpose) or for removing a noise, that is, filtering out pixels with too small or too large
. values. There are several types of thresholding supported by the function. They are determined by
. type parameter.（3）有几种阈值可通过参数控制
.
. Also, the special values #THRESH_OTSU or #THRESH_TRIANGLE may be combined with one of the
. above values. In these cases, the function determines the optimal threshold value using the Otsu's
. or Triangle algorithm and uses it instead of the specified thresh.
.
. @note Currently, （4）the Otsu's and Triangle methods are implemented only for 8-bit single-channel images.
.
. @param src input array (multiple-channel, 8-bit or 32-bit floating point).
. @param （5）dst output array of the same size and type and the same number of channels as src.
. @param thresh threshold value.
. @param maxval（6） maximum value to use with the #THRESH_BINARY and #THRESH_BINARY_INV thresholding
. types.
. @param type（7） thresholding type (see #ThresholdTypes).
. @return （8）the computed threshold value if Otsu's or Triangle methods used.
.
. @sa adaptiveThreshold, findContours, compare, min, max
"""
pass
（1）retval, dst = cv2.threshold( src , thresh, maxval, type)
阈值， 二值化图像 = cv2.threshold(输入灰度图， 阈值，最大值， 阈值类型)
阈值类型有8种：
原图：
5种固定阈值
1）THRESH_BINARY 将大于阈值的像素值设为maxval，将小于阈值的像素值设为0
2）THRESH_BINARY_INV，与THRESH_BINARY相反，将大于阈值的像素值设为0，将小于阈值的像素值设为maxval
3）THRESH_TRUNC，将大于阈值的像素值设为maxval，将小于阈值的像素值保留
4）THRESH_TOZERO，将大于阈值的像素值保留，将小于阈值的像素值设为0
5）THRESH_TOZERO_INV，与THRESH_TOZERO相反，将大于阈值的像素值设为0，将小于阈值的像素值保留
6）THRESH_OTSU：对于双峰图片，可采用该阈值自动寻找双峰之间的波谷，进行二分类划分。第一个返回值就是找到的阈值
在使用函数时需要把thresh=0设置为0. retval, dst = cv2.threshold(gray, thresh=0, 255, cv2.THRESH_OTSU)
7）THRESH_TRIANGLE，三角形算法，（有丢失）适用于单个波峰
8）THRESH_MASK
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('ent.png',0)
ret,thresh1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
ret,thresh2 = cv2.threshold(img,127,255,cv2.THRESH_BINARY_INV)
ret,thresh3 = cv2.threshold(img,127,255,cv2.THRESH_TRUNC)
ret,thresh4 = cv2.threshold(img,127,255,cv2.THRESH_TOZERO)
ret,thresh5 = cv2.threshold(img,0,255,cv2.THRESH_OTSU)
titles = ['Original', 'BINARY', 'BINARY_INV', 'TRUNC', 'TOZERO', 'THRESH_OTSU']
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()