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Proceedings Paper

Document image retrieval with morphology-based segmentation and features combination
Author(s): Tiago C. Bockholt; George D. C. Cavalcanti; Carlos A. B. Mello
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Paper Abstract

Digital libraries need more than just a retrieval based on keywords, which can be inefficient for some applications. Thus, a document retrieval based on content of the digitized image version of the document can be a more appropriated approach. This paper discusses the retrieval of document images by means of identifying a variety of elements present in the document's image body. We propose a new strategy to identify and combine features extracted from a document image. We also consider the task of constructing an optimized feature set to improve the retrieval performance and to validate our experiments on an assorted database. Experimental results show that the proposed segmentation together with a wisely feature combination increase the overall retrieval performance. Moreover the retrieved images demonstrate the generality and effectiveness of our approach for an efficient segmentation and classification of document images.

Paper Details

Date Published: 24 January 2011
PDF: 12 pages
Proc. SPIE 7874, Document Recognition and Retrieval XVIII, 787415 (24 January 2011); doi: 10.1117/12.876727
Show Author Affiliations
Tiago C. Bockholt, Federal Univ. of Pernambuco (Brazil)
George D. C. Cavalcanti, Federal Univ. of Pernambuco (Brazil)
Carlos A. B. Mello, Federal Univ. of Pernambuco (Brazil)


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

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