使用Python去掉试卷上的蓝色和红色笔记

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# -*- encoding: utf-8 -*- import cv2 import numpy as np     class SealRemove(object):     """     印章处理类     """       def remove_red_seal(self, image):         """         去除红色印章         """           # 获得红色通道         blue_c, green_c, red_c = cv2.split(image)           # 多传入一个参数cv2.THRESH_OTSU，并且把阈值thresh设为0，算法会找到最优阈值         thresh, ret = cv2.threshold(red_c, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)         # 实测调整为95%效果好一些         filter_condition = int(thresh * 0.5)           _, red_thresh = cv2.threshold(red_c, filter_condition, 255, cv2.THRESH_BINARY)           # 把图片转回 3 通道         result_img = np.expand_dims(red_thresh, axis=2)         result_img = np.concatenate((result_img, result_img, result_img), axis=-1)           return result_img       def remove_blue_seal(self, image):         """         去除红色印章         """           # 获得红色通道         blue_c, green_c, red_c = cv2.split(image)           # 多传入一个参数cv2.THRESH_OTSU，并且把阈值thresh设为0，算法会找到最优阈值         thresh, ret = cv2.threshold(blue_c, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)         # 实测调整为95%效果好一些         filter_condition = int(thresh * 0.2)           _, red_thresh = cv2.threshold(blue_c, filter_condition, 255, cv2.THRESH_BINARY)           # 把图片转回 3 通道         result_img = np.expand_dims(red_thresh, axis=2)         result_img = np.concatenate((result_img, result_img, result_img), axis=-1)           return result_img       def join_image(self, img_without_red, dst1_without_pen):             ret = cv2.bitwise_or(img_without_red, dst1_without_pen)             return ret     if __name__ == '__main__':     image = r'C:\Users\keying\Desktop\math\2.jpg'     img = cv2.imread(image)     seal_rm = SealRemove()     rm_img1 = seal_rm.remove_red_seal(img)     rm_img2 = seal_rm.remove_blue_seal(img)     rm_img = seal_rm.join_image(rm_img1,rm_img2)     cv2.imwrite(r"C:\Users\keying\Desktop\math\2.new.jpg", rm_img)

　　

 

参考:

https://blog.csdn.net/sogobaidu/article/details/115829791