Article

Color Co-occurence Descriptors for Querying-by-Example

Authors:

Vassili Kovalev,

Stephan VolmerAuthors Info & Claims

MMM '98: Proceedings of the 1998 Conference on MultiMedia Modeling

Page 32

Published: 12 October 1998 Publication History

Abstract

Multimedia documents are different from traditional text documents, because they may contain encodings of raw sensorical data. This fact has severe consequences for the efficient indexing and retrieval of information from documents in large unstructured collections (e.g. WWW), because it is very difficult to automatically identify generic meanings from visual or audible objects.A novel method for image retrieval from large collections is proposed in this paper. The method is based on color co-occurrence descriptors that utilize compact representations of essential information of the visual image content. The set of descriptor elements represents "elementary" color segments, their borders, and their mutual spatial distribution on the image frame. Such representation is flexible enough to describe image scenes ranging from simple combinations of color segments to high frequency color textures equally well.At the retrieval stage the comparison between a given query descriptor and the database descriptors is performed by a similarity measure. Image descriptors are robust versus affine transformations and several other image distortions. The consideration of the descriptors as sets of elements allows the combination of several images or subimages into a single query.Basic properties of the method are demonstrated experimentally on an image database containing 20000 images.

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Cited By

Valem LOliveira CPedronette DAlmeida J(2018)Unsupervised Similarity Learning through Rank Correlation and kNN SetsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/324105314:4(1-23)Online publication date: 23-Oct-2018
https://dl.acm.org/doi/10.1145/3241053
Wang XZhang HPeng G(2017)A chordiogram image descriptor using local edgelsJournal of Visual Communication and Image Representation10.1016/j.jvcir.2017.09.00549:C(129-140)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1016/j.jvcir.2017.09.005
Pedronette DTorres RKender JSmith JLuo JBoll SHsu W(2016)Rank Diffusion for Context-Based Image RetrievalProceedings of the 2016 ACM on International Conference on Multimedia Retrieval10.1145/2911996.2912060(321-325)Online publication date: 6-Jun-2016
https://dl.acm.org/doi/10.1145/2911996.2912060
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Color Co-occurence Descriptors for Querying-by-Example
1. Computing methodologies
  1. Computer graphics
2. Information systems
  1. Information retrieval

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cover image Guide Proceedings

MMM '98: Proceedings of the 1998 Conference on MultiMedia Modeling

October 1998

ISBN:0818689110

Copyright © Copyright (c) 1998 Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

Publisher

IEEE Computer Society

United States

Publication History

Published: 12 October 1998

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Cited By

Valem LOliveira CPedronette DAlmeida J(2018)Unsupervised Similarity Learning through Rank Correlation and kNN SetsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/324105314:4(1-23)Online publication date: 23-Oct-2018
https://dl.acm.org/doi/10.1145/3241053
Wang XZhang HPeng G(2017)A chordiogram image descriptor using local edgelsJournal of Visual Communication and Image Representation10.1016/j.jvcir.2017.09.00549:C(129-140)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1016/j.jvcir.2017.09.005
Pedronette DTorres RKender JSmith JLuo JBoll SHsu W(2016)Rank Diffusion for Context-Based Image RetrievalProceedings of the 2016 ACM on International Conference on Multimedia Retrieval10.1145/2911996.2912060(321-325)Online publication date: 6-Jun-2016
https://dl.acm.org/doi/10.1145/2911996.2912060
Pedronette DTorres R(2016)A correlation graph approach for unsupervised manifold learning in image retrieval tasksNeurocomputing10.1016/j.neucom.2016.03.081208:C(66-79)Online publication date: 5-Oct-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.03.081
Pedronette DTorres R(2016)Combining re-ranking and rank aggregation methods for image retrievalMultimedia Tools and Applications10.1007/s11042-015-3044-075:15(9121-9144)Online publication date: 1-Aug-2016
https://dl.acm.org/doi/10.1007/s11042-015-3044-0
Valem LPedronette DTorres RBorin EAlmeida JHauptmann ANgo CXue XJiang YSnoek CVasconcelos N(2015)Effective, Efficient, and Scalable Unsupervised Distance Learning in Image Retrieval TasksProceedings of the 5th ACM on International Conference on Multimedia Retrieval10.1145/2671188.2749336(51-58)Online publication date: 22-Jun-2015
https://dl.acm.org/doi/10.1145/2671188.2749336
Pedronette DPenatti OCalumby Rda S. Torres RKankanhalli MRueger SManmatha RJose Jvan Rijsbergen K(2014)Unsupervised Distance Learning By Reciprocal kNN Distance for Image RetrievalProceedings of International Conference on Multimedia Retrieval10.1145/2578726.2578770(345-352)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1145/2578726.2578770
Pedronette DDa S. Torres R(2013)Image re-ranking and rank aggregation based on similarity of ranked listsPattern Recognition10.1016/j.patcog.2013.01.00446:8(2350-2360)Online publication date: 1-Aug-2013
https://dl.acm.org/doi/10.1016/j.patcog.2013.01.004
Penatti OValle ETorres R(2012)Comparative study of global color and texture descriptors for web image retrievalJournal of Visual Communication and Image Representation10.1016/j.jvcir.2011.11.00223:2(359-380)Online publication date: 1-Feb-2012
https://dl.acm.org/doi/10.1016/j.jvcir.2011.11.002
Pedronette DDa S. Torres R(2012)Exploiting pairwise recommendation and clustering strategies for image re-rankingInformation Sciences: an International Journal10.1016/j.ins.2012.04.032207(19-34)Online publication date: 1-Nov-2012
https://dl.acm.org/doi/10.1016/j.ins.2012.04.032
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