Shadow Removal of Text Document Images Using Background Estimation and Adaptive Text Enhancement
Wenjie Liu, Bingshu Wang, Jiangbin Zheng, Wenmin Wang
Abstract
This paper proposes a simple yet effective method to re-move shadows from text document images. It mainly includes several parts. Firstly, we propose a text elimination-based background extraction strategy to estimate shadow map. It indicates the shadow regions accurately and helps to predict global background. Secondly, a binarization-based text ex-traction algorithm is designed to obtain texts from document image. By fusing texts and global background, a preparatory shadow-free image can be obtained. Thirdly, we propose an adaptive text contrast enhancement strategy to generate shadow-free results with comfortable visual perception across shadow and non-shadow regions. Quantitative and visual results performed on open datasets indicate that the proposed method can generate clear shadow-free images from text document images. Our code will be publicly available soon.
BibTeX
@inproceedings{icassp2023_shadowremovaloft,
title = {Shadow Removal of Text Document Images Using Background Estimation and Adaptive Text Enhancement},
author = {Wenjie Liu and Bingshu Wang and Jiangbin Zheng and Wenmin Wang},
booktitle = {ICASSP 2023},
year = {2023}
}