SHADOW REMOVAL OF TEXT DOCUMENT IMAGES USING BACKGROUND ESTIMATION and ADAPTIVE TEXT ENHANCEMENT
Wenjie Liu (Northwestern Polytechnical University); Bingshu Wang (Northwestern Polytechnical University); Jiangbin Zheng (Northwestern Polytechnical University); Wenmin Wang (Macau University of Science and Technology)
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This paper proposes a simple yet effective method to remove 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 extraction 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.