使用python和opencv去除试卷痕迹

2023-11-24 01:28| 来源: 网络整理| 查看: 265

小朋友做试卷，有时需要重新做一遍。才2年级，使用的是铅笔，批改用的是红笔，就想着自己使用opencv处理下，直接恢复到初始的空白试卷。

想法比较简单，通过灰度图和阀值，过滤掉铅笔的痕迹。使用提取红色通道及阀值，过滤掉红色的批改痕迹。再将两个图做一次“或”，就可以得到需要的空白试卷了。

关于红色的过滤参考了：https://blog.csdn.net/wl_Honest/article/details/107569135?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522161872855116780264052508%2522%252C%2522scm%2522%253A%252220140713.130102334..%2522%257D&request_id=161872855116780264052508&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~first_rank_v2~rank_v29-8-107569135.pc_search_result_hbase_insert&utm_term=opencv+%E5%8E%BB%E9%99%A4%E7%BA%A2%E8%89%B2

# -*- encoding: utf-8 -*- import cv2 import numpy as np class SealRemove(object): def remove_red_seal(self, image): # 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 * 0.95) nominator_thresh, red_thresh = cv2.threshold(red_c, filter_condition, 255, cv2.THRESH_BINARY) return red_thresh def shijuanqingli(self, image): # img = cv2.imread(image, 0) thresh, dst1 = cv2.threshold(image, 50, 255, cv2.THRESH_BINARY) dst1_without_pen = dst1 return dst1_without_pen 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__': src = r'/home/pi/Pictures/img20210417_12203672.bmp' image0 = cv2.imread(src) seal_rm = SealRemove() image_0 = seal_rm.remove_red_seal(image0) # image_0_1 = cv2.cvtColor(image_0, cv2.COLOR_BGR2GRAY) image1 = cv2.imread(src, 0) image_1 = seal_rm.shijuanqingli(image1) image_result = seal_rm.join_image(image_0, image_1) cv2.imshow('new image', image_result) cv2.waitKey(0) cv2.destroyAllWindows() src_temp = src.split(r'.') src_result = src_temp[0] + '_new.' + src_temp[1] cv2.imwrite(src_result,image_result)

处理后的图片如下。（处理前的图片有小朋友的答案在上面了，就不发了）

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