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Abstract

In this paper, we propose a new approach for designing histogram-based descriptors. For demonstration purpose, we generate a descriptor based on the histogram of differential-turning angle scale space (d-TASS) function and its derived data. We then compare the proposed histogram-based descriptor with the traditional histogram descriptors in terms of retrieval performance from image databases. Experiments on three shapes databases demonstrate the efficiency and the effectiveness of the new technique: the proposed technique of histogram-based descriptor outperforms the traditional one. These experiments showed also that the proposed histogram-based descriptor using d-TASS function and the derived features performs well compared with the state-of-the-art. When applied to texture images retrieval, the proposed approach yields higher performance than the traditional histogram-based descriptors. From these results, we believe that the proposed histogram-based descriptor should perform efficiently for medical images retrieval so we will focus on this aspect in the future work.

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Correspondence to Kidiyo Kpalma .

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Kpalma, K. et al. (2013). A New Histogram-Based Descriptor for Images Retrieval from Databases. In: Kountchev, R., Iantovics, B. (eds) Advances in Intelligent Analysis of Medical Data and Decision Support Systems. Studies in Computational Intelligence, vol 473. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00029-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-00029-9_9

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00028-2

  • Online ISBN: 978-3-319-00029-9

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