research-article

A kernel-based approach to document retrieval

Authors:

Ernest Valveny,

Marçal RusiñolAuthors Info & Claims

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

Pages 377 - 384

https://doi.org/10.1145/1815330.1815379

Published: 09 June 2010 Publication History

Abstract

In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the probability that a given document belongs to a certain class. The membership probability to a specific class is computed using Support Vector Machines in conjunction with similarity measure based kernel applied to structural document representations. In the presented experiments, we use different document representations, both visual and structural, and we apply them to a database of historical documents. We show how our method based on similarity kernels outperforms the usual distance-based retrieval.

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Cited By

Alaei FAlaei ABlumenstein MPal U(2016)Document image retrieval based on texture features and similarity fusion2016 International Conference on Image and Vision Computing New Zealand (IVCNZ)10.1109/IVCNZ.2016.7804437(1-6)Online publication date: Nov-2016
https://doi.org/10.1109/IVCNZ.2016.7804437
Alaei FAlaei ABlumenstein MPal U(2016)A brief review of document image retrieval methods: Recent advances2016 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN.2016.7727648(3500-3507)Online publication date: Jul-2016
https://doi.org/10.1109/IJCNN.2016.7727648
Alaei FAlaei APal UBlumenstein M(2016)Document Image Retrieval Based on Texture Features: A Recognition-Free Approach2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)10.1109/DICTA.2016.7797033(1-7)Online publication date: Nov-2016
https://doi.org/10.1109/DICTA.2016.7797033
Show More Cited By

Index Terms

A kernel-based approach to document retrieval
1. Applied computing
  1. Computers in other domains
    1. Digital libraries and archives
  2. Document management and text processing
    1. Document capture
      1. Document analysis
2. Information systems
  1. Information systems applications
    1. Digital libraries and archives

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cover image ACM Other conferences

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

June 2010

490 pages

ISBN:9781605587738

DOI:10.1145/1815330

General Chairs:
David Doermann
University of Maryland, College Park
,
Venu Govindaraju
University at Buffalo, SUNY
,
Daniel Lopresti
Lehigh University
,
Prem Natarajan
Raytheon BBN Technologies

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 June 2010

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CONSOLIDER - INGENIO 2010
Ministerio de Educación, Cultura y Deporte

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DAS '10

DAS '10: The Eighth IAPR International Workshop on Document Analysis Systems

June 9 - 11, 2010

Massachusetts, Boston, USA

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Cited By

Alaei FAlaei ABlumenstein MPal U(2016)Document image retrieval based on texture features and similarity fusion2016 International Conference on Image and Vision Computing New Zealand (IVCNZ)10.1109/IVCNZ.2016.7804437(1-6)Online publication date: Nov-2016
https://doi.org/10.1109/IVCNZ.2016.7804437
Alaei FAlaei ABlumenstein MPal U(2016)A brief review of document image retrieval methods: Recent advances2016 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN.2016.7727648(3500-3507)Online publication date: Jul-2016
https://doi.org/10.1109/IJCNN.2016.7727648
Alaei FAlaei APal UBlumenstein M(2016)Document Image Retrieval Based on Texture Features: A Recognition-Free Approach2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)10.1109/DICTA.2016.7797033(1-7)Online publication date: Nov-2016
https://doi.org/10.1109/DICTA.2016.7797033
Rusiñol MFrinken VKaratzas DBagdanov ALladós J(2014)Multimodal page classification in administrative document image streamsInternational Journal on Document Analysis and Recognition10.1007/s10032-014-0225-817:4(331-341)Online publication date: 1-Dec-2014
https://dl.acm.org/doi/10.1007/s10032-014-0225-8
Marinai S(2014)Page Similarity and ClassificationHandbook of Document Image Processing and Recognition10.1007/978-0-85729-859-1_7(223-253)Online publication date: 30-Apr-2014
https://doi.org/10.1007/978-0-85729-859-1_7

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