【code】圖片二值化，凸顯重要部分

公衆號：深度學習視覺
第一博客
opencv中文官網

OCR的必須品-OTSU

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
import seaborn as sns
%matplotlib inline
sns.set(style="darkgrid") 

fig = plt.figure(figsize=(12,6))
img = cv.imread('test2.jpg',0)
# 全局閾值
ret1,th1 = cv.threshold(img,127,255,cv.THRESH_BINARY)
# Otsu閾值
ret2,th2 = cv.threshold(img,0,255,cv.THRESH_BINARY+cv.THRESH_OTSU)
# 高斯濾波後再採用Otsu閾值
blur = cv.GaussianBlur(img,(5,5),0)
ret3,th3 = cv.threshold(blur,0,255,cv.THRESH_BINARY+cv.THRESH_OTSU)
# 繪製所有圖像及其直方圖
images = [img, 0, th1,
          img, 0, th2,
          blur, 0, th3]
titles = ['Original Noisy Image','Histogram','Global Thresholding (v=127)',
          'Original Noisy Image','Histogram',"Otsu's Thresholding",
          'Gaussian filtered Image','Histogram',"Otsu's Thresholding"]
for i in range(3):
    plt.subplot(3,3,i*3+1),plt.imshow(images[i*3],'gray')
    plt.title(titles[i*3]), plt.xticks([]), plt.yticks([])
    plt.subplot(3,3,i*3+2),plt.hist(images[i*3].ravel(),256)
    plt.title(titles[i*3+1]), plt.xticks([]), plt.yticks([])
    plt.subplot(3,3,i*3+3),plt.imshow(images[i*3+2],'gray')
    plt.title(titles[i*3+2]), plt.xticks([]), plt.yticks([])

plt.show()