An improved binarization algorithm based on a water flow model for document image with inhomogeneous backgrounds

Authors:
Hyun-Hwa Oh;Kil-Taek Lim;Sung-Il Chien
Affiliations:
Imaging Solution Program Team, Samsung Advanced Institute of Technology, Yongin 449-712, Republic of Korea;School of Computer and Multimedia Engineering, Gyeongju University, Gyeongju 780-712, Republic of Korea;School of Electrical Engineering and Computer Science, Kyungpook National University, Daegu 702-701, Republic of Korea
Venue:
Pattern Recognition
Year:
2005

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Abstract

A segmentation algorithm using a water flow model [Kim et al., Pattern Recognition 35 (2002) 265-277] has already been presented where a document image can be efficiently divided into two regions, characters and background, due to the property of locally adaptive thresholding. However, this method has not decided when to stop the iterative process and required long processing time. Plus, characters on poor contrast backgrounds often fail to be separated successfully. Accordingly, to overcome the above drawbacks to the existing method, the current paper presents an improved approach that includes extraction of regions of interest (ROIs), an automatic stopping criterion, and hierarchical thresholding. Experimental results show that the proposed method can achieve a satisfactory binarization quality, especially for document images with a poor contrast background, and is significantly faster than the existing method.