Stroke Width-Based Contrast Feature for Document Image Binarization


Le Thi Khue Van, Gueesang Lee, Journal of Information Processing Systems Vol. 10, No. 1, pp. 55-68, Feb. 2014  

10.3745/JIPS.2014.10.1.055
Keywords: Degraded Document Image, Binarization, Stroke Width, Contrast Feature, Text Boundary
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Abstract

Automatic segmentation of foreground text from the background in degraded document images is very much essential for the smooth reading of the document content and recognition tasks by machine. In this paper, we present a novel approach to the binarization of degraded document images. The proposed method uses a new local contrast feature extracted based on the stroke width of text. First, a pre-processing method is carried out for noise removal. Text boundary detection is then performed on the image constructed from the contrast feature. Then local estimation follows to extract text from the background. Finally, a refinement procedure is applied to the binarized image as a post-processing step to improve the quality of the final results. Experiments and comparisons of extracting text from degraded handwriting and machine-printed document image against some well-known binarization algorithms demonstrate the effectiveness of the proposed method.


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Cite this article
[APA Style]
Le Thi Khue Van and Gueesang Lee (2014). Stroke Width-Based Contrast Feature for Document Image Binarization. Journal of Information Processing Systems, 10(1), 55-68. DOI: 10.3745/JIPS.2014.10.1.055.

[IEEE Style]
L. T. K. Van and G. Lee, "Stroke Width-Based Contrast Feature for Document Image Binarization," Journal of Information Processing Systems, vol. 10, no. 1, pp. 55-68, 2014. DOI: 10.3745/JIPS.2014.10.1.055.

[ACM Style]
Le Thi Khue Van and Gueesang Lee. 2014. Stroke Width-Based Contrast Feature for Document Image Binarization. Journal of Information Processing Systems, 10, 1, (2014), 55-68. DOI: 10.3745/JIPS.2014.10.1.055.