Abstract
Binarization of document images with poor contrast, high noise and variable modalities remains a challenging problem. This paper proposes a new binarization method that adopts the use of seeded region growing and character’s topographic feature. It consists of three steps: first, seed pixels are selected automatically according to their topographic features; second, regions are grown controlled by new weighted priority until all pixels are labeled black or white; third, noisy regions are removed based on the average stroke width feature. Our method overcomes the difficulty of global binarization to find a single value to fit all. It also avoids the common problem in most local thresholding technique of finding a suitable window size. The proposed method performed well in binarization and the experimental results of evaluation showed significant improvement compared to several other methods.
The research is supported by the National High Technology Research and Development Program of China (No.2003AA1Z2230).
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© 2004 Springer-Verlag Berlin Heidelberg
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Sun, Y., Chen, Y., Zhang, Y., Li, Y. (2004). Automated Seeded Region Growing Method for Document Image Binarization Based on Topographic Features. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_25
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DOI: https://doi.org/10.1007/978-3-540-30126-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23240-7
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