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Proceedings Paper

Boosting based text and non-text region classification
Author(s): Binqing Xie; Gady Agam
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Paper Abstract

Layout analysis is a crucial process for document image understanding and information retrieval. Document layout analysis depends on page segmentation and block classification. This paper describes an algorithm for extracting blocks from document images and a boosting based method to classify those blocks as machine printed text or not. The feature vector which is fed into the boosting classifier consists of a four direction run-length histogram, and connected components features in both background and foreground. Using a combination of features through a boosting classifier, we obtain an accuracy of 99.5% on our test collection.

Paper Details

Date Published: 24 January 2011
PDF: 8 pages
Proc. SPIE 7874, Document Recognition and Retrieval XVIII, 787416 (24 January 2011); doi: 10.1117/12.876736
Show Author Affiliations
Binqing Xie, Illinois Institute of Technology (United States)
Gady Agam, Illinois Institute of Technology (United States)

Published in SPIE Proceedings Vol. 7874:
Document Recognition and Retrieval XVIII
Gady Agam; Christian Viard-Gaudin, Editor(s)

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