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Fast discrete curvelet transform-based anisotropic feature extraction for biomedical image indexing and retrieval

Fast discrete curvelet transform-based anisotropic feature extraction for biomedical image... This paper presents fast discrete curvelet transform-based anisotropic feature extraction for biomedical image indexing and retrieval. In this work, the curvelet transform is applied on the image and feature vector is calculated using the directional energies of these curvelet coefficients. The effectiveness of the proposed approach has been tested on three well-known databases: Open access series of imaging studies MRI, Emphysema-CT and NEMA-CT. The performance of the proposed system is evaluated using average retrieval precision and average retrieval rate. The experimental results show the superiority of proposed approach over well-known existing methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Multimedia Information Retrieval Springer Journals

Fast discrete curvelet transform-based anisotropic feature extraction for biomedical image indexing and retrieval

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer-Verlag London Ltd.
Subject
Computer Science; Multimedia Information Systems; Information Storage and Retrieval; Information Systems Applications (incl.Internet); Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Computer Science, general
ISSN
2192-6611
eISSN
2192-662X
DOI
10.1007/s13735-017-0132-0
Publisher site
See Article on Publisher Site

Abstract

This paper presents fast discrete curvelet transform-based anisotropic feature extraction for biomedical image indexing and retrieval. In this work, the curvelet transform is applied on the image and feature vector is calculated using the directional energies of these curvelet coefficients. The effectiveness of the proposed approach has been tested on three well-known databases: Open access series of imaging studies MRI, Emphysema-CT and NEMA-CT. The performance of the proposed system is evaluated using average retrieval precision and average retrieval rate. The experimental results show the superiority of proposed approach over well-known existing methods.

Journal

International Journal of Multimedia Information Retrieval – Springer Journals

Published: Sep 18, 2017

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