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Color image retrieval technique with local features based on orthogonal polynomials model and SIFT

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Abstract

In this paper, a new color image retrieval technique is proposed with local features given by Scale Invariant Feature Transform (SIFT) key points that are described in the integer-natured, computationally light Orthogonal Polynomials Transform (OPT) domain. The transform’s point spread operators are derived from a generating function, modification to which has been proposed for alleviating computational complexity further. The expressive power of the transform coefficients has been exploited for forming the descriptors of SIFT key points of a given image. The key point descriptors, OPT-SIFT so formed have good expressive power, despite being shorter in length and having a reduced computational complexity. A retrieval technique has been proposed based on OPT-SIFT features. The proposed retrieval technique has been experimented with images from standard databases such COIL-100 and Corel and the results demonstrate the superiority of the proposed descriptors when compared to other descriptors.

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Authors and Affiliations

  1. Image Vision Laboratory, Dept. of CSE, Anna University of Technology, Tiruchirapalli, 620 024, India

    J. Kalpana & R. Krishnamoorthi

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  1. J. Kalpana
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  2. R. Krishnamoorthi
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Correspondence to J. Kalpana.

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Kalpana, J., Krishnamoorthi, R. Color image retrieval technique with local features based on orthogonal polynomials model and SIFT. Multimed Tools Appl 75, 49–69 (2016). https://doi.org/10.1007/s11042-014-2262-1

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  • DOI: https://doi.org/10.1007/s11042-014-2262-1

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