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Comparative assessment of efficiency for content based image retrieval systems using different wavelet features and pre-classifier

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An Erratum to this article was published on 08 December 2016

Abstract

Recently, Content Based Image Retrieval (CBIR) has emerged as an active research area having applications in various fields. There exist several states-of-the art CBIR systems that uses both spatial and transform features as input. However, as hardly any details study reported so far on the effectiveness of different transform domain features in CBIR paradigm. This motivates the current article where we have presented extensive comparative assessment of five different transform domain features considering various filter combinations. Three different feature representation schemes and three different classifiers have been used for this purpose. Extensive experiments on four widely used benchmark image databases (Oliva, Caltech101, Caltech256 and MIRFlickr25000) were conducted to determine the best combination of transform, filters, feature representation and classifier. Furthermore, we have also attempted to discover the optimal features from the best combinations using maximal information compression index (MICI). Both qualitative and quantitative evaluations show that the combination of Least Square Support Vector Machine (LSSVM) as a classifier and the statistical parametric framework based reduced feature representation in Non-Subsampled Contourlet Transform (NSCT) with “pyrexc” and “sinc” filters gives the best retrieval performances.

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Acknowledgements

The authors would like to thank all the anonymous reviewers and the associate editor for their valuable comments. The work is mainly funded by Machine Intelligence Unit, Indian Statistical Institute, Kolkata-108 (Internal Academic Project) for providing facilities to carry out this work. Malay K. Kundu acknowledges the Indian National Academy of Engineering (INAE) for their support through INAE Distinguished Professor fellowship.

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  1. Machine Intelligence Unit, Indian Statistical Institute, 203 B.T. Road, Kolkata, 108, India

    Manish Chowdhury & Malay Kumar Kundu

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  1. Manish Chowdhury
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Correspondence to Manish Chowdhury.

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An erratum to this article is available at http://dx.doi.org/10.1007/s11042-016-4172-x.

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Chowdhury, M., Kundu, M.K. Comparative assessment of efficiency for content based image retrieval systems using different wavelet features and pre-classifier. Multimed Tools Appl 74, 11595–11630 (2015). https://doi.org/10.1007/s11042-014-2252-3

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