Texture similarity using periodically extended and adaptive curvelets

Hasan Al-Marzouqi, Ghassan Al Regib

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

This paper presents a new method for texture based image retrieval. The proposed algorithm uses a periodically extended variant of the curvelet transform. The sum of the absolute value of differences in the mean and standard deviation between curvelet wedges representing the query image and the test image is used as the distance index. Performance improvement is demonstrated using the CUReT database, where the proposed algorithm significantly outperforms previously proposed methods that were based on Curvelet, Gabor, LBP, and wavelet features. We also show that adapting curvelet tiles increases the performance of the proposed method.

Original languageBritish English
Title of host publication2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages951-955
Number of pages5
ISBN (Electronic)9781479970889
DOIs
StatePublished - 5 Feb 2014
Event2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 - Atlanta, United States
Duration: 3 Dec 20145 Dec 2014

Publication series

Name2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

Conference

Conference2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
Country/TerritoryUnited States
CityAtlanta
Period3/12/145/12/14

Keywords

  • CBIR
  • Curvelet
  • Texture

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