Stroke Width-Based Contrast Feature for Document Image Binarization

Le Thi Khue Van and Gueesang Lee
Volume: 10, No: 1, Page: 55 ~ 68, Year: 2014
10.3745/JIPS.2014.10.1.055
Keywords: Degraded Document Image, Binarization, Stroke Width, Contrast Feature, Text Boundary
Full Text:

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.

Article Statistics
Multiple requests among the same broswer session are counted as one view (or download).
If you mouse over a chart, a box will show the data point's value.


Cite this article
IEEE Style
Le Thi Khue Van and Gueesang 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, "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.