Word Image Decomposition from Image Regions in Document Images using Statistical Analyses


KIPS Transactions on Software and Data Engineering, Vol. 13, No. 6, pp. 591-600, Jun. 2006
10.3745/KIPSTB.2006.13.6.591, Full Text:

Abstract

This paper describes the development and implementation of a algorithm to decompose word images from image regions mixed text/graphics in document images using statistical analyses. To decompose word images from image regions, the character components need to be separated from graphic components. For this process, we propose a method to separate them with an analysis of box-plot using a statistics of structural components. An accuracy of this method is not sensitive to the changes of images because the criterion of separation is defined by the statistics of components. And then the character regions are determined by analyzing a local crowdedness of the separated character components. Finally, we devide the character regions into text lines and word images using projection profile analysis, gap clustering, special symbol detection, etc. The proposed system could reduce the influence resulted from the changes of images because it uses the criterion based on the statistics of image regions. Also, we made an experiment with the proposed method in document image processing system for keyword spotting and showed the necessity of studying for the proposed method.


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Cite this article
[IEEE Style]
C. B. Jeong and S. H. Kim, "Word Image Decomposition from Image Regions in Document Images using Statistical Analyses," KIPS Journal B (2001 ~ 2012) , vol. 13, no. 6, pp. 591-600, 2006. DOI: 10.3745/KIPSTB.2006.13.6.591.

[ACM Style]
Chang Bu Jeong and Soo Hyung Kim. 2006. Word Image Decomposition from Image Regions in Document Images using Statistical Analyses. KIPS Journal B (2001 ~ 2012) , 13, 6, (2006), 591-600. DOI: 10.3745/KIPSTB.2006.13.6.591.