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Boosting local texture descriptors with Log-Gabor filters response for improved image retrieval

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Abstract

In the recent past, many local texture descriptors have been proposed for the image retrieval task. In order to improve the image retrieval accuracy, quite a few of these descriptors have been implemented on Gabor filter response. However, the response of Log-Gabor filters has been proved to be better than Gabor filters with respect to their discrimination ability. In this paper, we present a framework for image retrieval that applies various local texture descriptors on Log-Gabor filters response. To evaluate the retrieval performance of the proposed framework, experiments have been conducted on standard Wang, VisTex and OT-Scene databases. Consistent improvement in the image retrieval accuracy demonstrates the effectiveness of this framework. Further, the experimental results show that the use of proposed framework with low-dimension texture descriptors such as Orthogonal Combination of Local Binary Pattern makes them a better choice over Local Binary Pattern and its high-dimensional variants when higher retrieval accuracy, small feature vector size and ease of computation is desired.

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Authors and Affiliations

  1. Department of Computer Science, University of Saskatchewan, Saskatoon, Canada

    Ekta Walia

  2. Department of Computer Science, M.L.N. College, Yamunanagar, India

    Vishal Verma

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  1. Ekta Walia
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  2. Vishal Verma
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Correspondence to Vishal Verma.

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Walia, E., Verma, V. Boosting local texture descriptors with Log-Gabor filters response for improved image retrieval. Int J Multimed Info Retr 5, 173–184 (2016). https://doi.org/10.1007/s13735-016-0099-2

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  • DOI: https://doi.org/10.1007/s13735-016-0099-2

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