Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)

Image Retrieval Based on Color-Statistic Feature

Authors
Jinmei Liu, Jizhong Li
Corresponding Author
Jinmei Liu
Available Online February 2013.
DOI
https://doi.org/10.2991/isccca.2013.164How to use a DOI?
Keywords
color, change statistic, image retrieval
Abstract

Color is the most widely used visual feature in content based image retrieval. The visual coherence color space, HSV, is adopted to represent image. Hue component is used to denote color. Hue difference statistic is proposed to extract color change information as supplement to color feature. The image is divided into sub images equally. Color and change information is extracted in each region. After feature vector clustering and coding, image content can be expressed as vector codes. The text based analysis technology is used for image retrieval. Experiments show that the proposed method can realize efficient retrieval for unconstrained scene images.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)
Series
Advances in Intelligent Systems Research
Publication Date
February 2013
ISBN
978-90-78677-63-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/isccca.2013.164How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jinmei Liu
AU  - Jizhong Li
PY  - 2013/02
DA  - 2013/02
TI  - Image Retrieval Based on Color-Statistic Feature
BT  - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)
PB  - Atlantis Press
SP  - 655
EP  - 658
SN  - 1951-6851
UR  - https://doi.org/10.2991/isccca.2013.164
DO  - https://doi.org/10.2991/isccca.2013.164
ID  - Liu2013/02
ER  -