How to remove shadow from scanned images using OpenCV?

Question

I'd like to remove shadow before image binarization using OpenCV. I've tried Otsu Method and adaptive thresholding, however for images where there are large regions of shadow, these two methods will not give good results.

Any better solutions? Thanks in advance.

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Answer 1

Since you didn't specify any language, I'll assume Python to illustrate.

A decent starting point might be taking the approach I show in this answer and expand it to work with multiple channels.

Something along the lines of

import cv2 import numpy as np  img = cv2.imread('shadows.png', -1)  rgb_planes = cv2.split(img)  result_planes = [] result_norm_planes = [] for plane in rgb_planes:     dilated_img = cv2.dilate(plane, np.ones((7,7), np.uint8))     bg_img = cv2.medianBlur(dilated_img, 21)     diff_img = 255 - cv2.absdiff(plane, bg_img)     norm_img = cv2.normalize(diff_img,None, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_8UC1)     result_planes.append(diff_img)     result_norm_planes.append(norm_img)  result = cv2.merge(result_planes) result_norm = cv2.merge(result_norm_planes)  cv2.imwrite('shadows_out.png', result) cv2.imwrite('shadows_out_norm.png', result_norm) 

The non-normalized result looks as follows:

And the normalized result: