research-article

Efficient logo retrieval through hashing shape context descriptors

Authors:

Marçal Rusiñol,

Josep LladósAuthors Info & Claims

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

Pages 215 - 222

https://doi.org/10.1145/1815330.1815358

Published: 09 June 2010 Publication History

Abstract

In this paper we present a method for organizing and indexing logo digital libraries like the ones of the patent and trademark offices. We propose an efficient queried-by-example retrieval system which is able to retrieve logos by similarity from large databases of logo images. Logos are compactly described by a variant of the shape context descriptor. These descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The experiments demonstrate the effectiveness and efficiency of this system on realistic datasets as the Tobacco-800 logo database.

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Cited By

Guijarro MBayon JMartín-Carabias DRecas J(2024)A Multi-Stage Method for Logo Detection in Scanned Official Documents Based on Image ProcessingAlgorithms10.3390/a1704017017:4(170)Online publication date: 22-Apr-2024
https://doi.org/10.3390/a17040170
Benabdelaziz RGaceb DHaddad M(2021)A Comparison of CNN and Conventional Descriptors for Word Spotting Approach: Application to Handwritten Document Image RetrievalInnovative Systems for Intelligent Health Informatics10.1007/978-3-030-70713-2_99(1115-1126)Online publication date: 6-May-2021
https://doi.org/10.1007/978-3-030-70713-2_99
Nandedkar ANandedkar A(2020)Multimodal Query Based Approach for Document Image RetrievalComputer Vision and Image Processing10.1007/978-981-15-4015-8_32(361-371)Online publication date: 29-Mar-2020
https://doi.org/10.1007/978-981-15-4015-8_32
Show More Cited By

Index Terms

Efficient logo retrieval through hashing shape context descriptors
1. Applied computing
  1. Computers in other domains
    1. Digital libraries and archives
  2. Document management and text processing
    1. Document capture
      1. Graphics recognition and interpretation
2. Information systems
  1. Information systems applications
    1. Digital libraries and archives
    2. Multimedia information systems
      1. Multimedia databases

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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

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Publication History

Published: 09 June 2010

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CONSOLIDER - INGENIO 2010
Spanish projects

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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

Guijarro MBayon JMartín-Carabias DRecas J(2024)A Multi-Stage Method for Logo Detection in Scanned Official Documents Based on Image ProcessingAlgorithms10.3390/a1704017017:4(170)Online publication date: 22-Apr-2024
https://doi.org/10.3390/a17040170
Benabdelaziz RGaceb DHaddad M(2021)A Comparison of CNN and Conventional Descriptors for Word Spotting Approach: Application to Handwritten Document Image RetrievalInnovative Systems for Intelligent Health Informatics10.1007/978-3-030-70713-2_99(1115-1126)Online publication date: 6-May-2021
https://doi.org/10.1007/978-3-030-70713-2_99
Nandedkar ANandedkar A(2020)Multimodal Query Based Approach for Document Image RetrievalComputer Vision and Image Processing10.1007/978-981-15-4015-8_32(361-371)Online publication date: 29-Mar-2020
https://doi.org/10.1007/978-981-15-4015-8_32
Chanda SPrasad PHast ABrun AMartensson LPal U(2020)Finding Logo and Seal in Historical Document Images - An Object Detection Based ApproachPattern Recognition10.1007/978-3-030-41404-7_58(821-834)Online publication date: 23-Feb-2020
https://doi.org/10.1007/978-3-030-41404-7_58
Wiggers KBritto AHeutte LKoerich AOliveira L(2019)Image Retrieval and Pattern Spotting using Siamese Neural Network2019 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN.2019.8852197(1-8)Online publication date: Jul-2019
https://doi.org/10.1109/IJCNN.2019.8852197
Wiggers KBritto AHeutte LKoerich AOliveira L(2018)Document Image Retrieval Using Deep Features2018 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN.2018.8489722(1-8)Online publication date: Jul-2018
https://doi.org/10.1109/IJCNN.2018.8489722
Wahlberg F(2018)Gaussian Process Classification as Metric Learning for Forensic Writer Identification2018 13th IAPR International Workshop on Document Analysis Systems (DAS)10.1109/DAS.2018.76(175-180)Online publication date: Apr-2018
https://doi.org/10.1109/DAS.2018.76
Polsley SRay JHammond T(2017)SketchSeeker: Finding Similar SketchesIEEE Transactions on Human-Machine Systems10.1109/THMS.2017.264968447:2(194-205)Online publication date: Apr-2017
https://doi.org/10.1109/THMS.2017.2649684
Kim BHong GPsannis K(2017)Design of efficient shape feature for object-based watermarking technologyMultimedia Tools and Applications10.1007/s11042-017-4344-376:21(22741-22759)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s11042-017-4344-3
Sharath Kumar YRanjith K(2017)An Approach for Logo Detection and Retrieval in DocumentsRecent Trends in Image Processing and Pattern Recognition10.1007/978-981-10-4859-3_5(49-58)Online publication date: 29-Apr-2017
https://doi.org/10.1007/978-981-10-4859-3_5
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