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A New Histogram-Based Descriptor for Images Retrieval from Databases

  • Kidiyo Kpalma
  • Cong Bai
  • Miloud Chikr El Mezouar
  • Kamel Belloulata
  • Nasreddine Taleb
  • Lakhdar Belhallouche
  • Djamal Boukerroui
Part of the Studies in Computational Intelligence book series (SCI, volume 473)

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.

Keywords

pattern recognition image description image retrieval texture image differential-turning angle scale space turning angle scale space bull’s eye performance 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Kidiyo Kpalma
    • 1
  • Cong Bai
    • 1
  • Miloud Chikr El Mezouar
    • 1
    • 2
  • Kamel Belloulata
    • 2
  • Nasreddine Taleb
    • 2
  • Lakhdar Belhallouche
    • 2
  • Djamal Boukerroui
    • 3
  1. 1.UEB - INSA, IETR, UMR 6164RennesFrance
  2. 2.RCAMUniversité de Sidi Bel AbbèsSidi Bel AbbèsAlgeria
  3. 3.Heudiasyc UMR 7253 UTCCompiègneFrance

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