loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Cong Bai ; Kidiyo Kpalma and Joseph Ronsin

Affiliation: Université Europénne de Bretagne, France

Keyword(s): Content-based Image Retrieval, DCT, Texture, Face Recognition.

Related Ontology Subjects/Areas/Topics: Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

Abstract: This paper proposes an improved approach for content-based image retrieval in Discrete Cosine Transform domain. For each 4x4 DCT block, we calculate the statistical information of three groups of AC coefficients and propose to use these values to form the AC-Pattern and use DC coefficients of neighboring blocks to construct DC-Pattern. The histograms of these two patterns are constructed and their selections are concatenated as feature descriptor. Similarity between the feature descriptors is measured by c2 distance. Experiments executed on widely used face and texture databases show that better performance can be observed with the proposal compared with other classical method and state-of-the-art approaches.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.149.213.209

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Bai, C.; Kpalma, K. and Ronsin, J. (2013). An Improved Feature Vector for Content-based Image Retrieval in DCT Domain. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP; ISBN 978-989-8565-47-1; ISSN 2184-4321, SciTePress, pages 742-745. DOI: 10.5220/0004206607420745

@conference{visapp13,
author={Cong Bai. and Kidiyo Kpalma. and Joseph Ronsin.},
title={An Improved Feature Vector for Content-based Image Retrieval in DCT Domain},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP},
year={2013},
pages={742-745},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004206607420745},
isbn={978-989-8565-47-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP
TI - An Improved Feature Vector for Content-based Image Retrieval in DCT Domain
SN - 978-989-8565-47-1
IS - 2184-4321
AU - Bai, C.
AU - Kpalma, K.
AU - Ronsin, J.
PY - 2013
SP - 742
EP - 745
DO - 10.5220/0004206607420745
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic