Texture retrieval using periodically extended and adaptive curvelets

Image retrieval is an important problem in the area of multimedia processing. This paper presents two new curvelet-based algorithms for texture retrieval suitable, which are suitable for use in constrained-memory devices. The developed algorithms are tested on three publicly available texture datase...

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Bibliographic Details
Published in:Signal processing. Image communication 2019-08, Vol.76, p.252-260
Main Authors: Al-Marzouqi, Hasan, Hu, Yuting, AlRegib, Ghassan
Format: Article
Language:English
Subjects:
Algorithms
CBIR
Classification
Curvelet
Image management
Image retrieval
Memory devices
Multimedia
Texture
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Summary:Image retrieval is an important problem in the area of multimedia processing. This paper presents two new curvelet-based algorithms for texture retrieval suitable, which are suitable for use in constrained-memory devices. The developed algorithms are tested on three publicly available texture datasets: CUReT, Mondial-Marmi, and STex-fabric. Our experiments confirm the effectiveness of the proposed system. Furthermore, a weighted version of the proposed retrieval algorithm is proposed, which is shown to achieve promising results in the classification of seismic activities. •This paper presents two new curvelet-based algorithms for texture retrieval.•Developed algorithms achieved favorable results on three publicly available texture datasets.•A weighted variant of the developed algorithm was used for seismic activity classification.
ISSN:0923-5965
1879-2677
DOI:10.1016/j.image.2019.04.015