Automatic content extraction of filled-form images based on clustering component block projection vectors

Hanchuan Peng; Xiaofeng He; Fuhui Long

doi:10.1117/12.527345

15 December 2003 Automatic content extraction of filled-form images based on clustering component block projection vectors

Hanchuan Peng, Xiaofeng He, Fuhui Long

Author Affiliations +

Proceedings Volume 5296, Document Recognition and Retrieval XI; (2003) https://doi.org/10.1117/12.527345
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

Abstract

Automatic understanding of document images is a hard problem. Here we consider a sub-problem, automatically extracting content from filled form images. Without pre-selected templates or sophisticated structural/semantic analysis, we propose a novel approach based on clustering the component-block-projection-vectors. By combining spectral clustering and minimal spanning tree clustering, we generate highly accurate clusters, from which the adaptive templates are constructed to extract the filled-in content. Our experiments show this approach is effective for a set of 1040 US IRS tax form images belonging to 208 types.

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Hanchuan Peng, Xiaofeng He, and Fuhui Long "Automatic content extraction of filled-form images based on clustering component block projection vectors", Proc. SPIE 5296, Document Recognition and Retrieval XI, (15 December 2003); https://doi.org/10.1117/12.527345

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