A Ripplet Transform Based Statistical Framework for Natural Color Image Retrieval

  • Manish Chowdhury
  • Sudeb Das
  • Malay K. Kundu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8156)

Abstract

We present a novel Content Based Image Retrieval (CBIR) scheme for natural color images using Multi-scale Geometric Analysis (MGA) of Ripplet Transform (RT) Type-I in the statistical framework based on Generalized Gaussian Density (GGD) model and Kullback-Leibler Distance (KLD). The system is based on modeling the marginal distributions of RT coefficients by GGD framework and computing the similarity between the model parameters using the KLD. Least Square-Support Vector Machine (LS-SVM) classifier is used to classify the images of the database. Extensive experiments were carried out to evaluate the effectiveness of the proposed system on two image databases consisting 1000 (Simplicity) and 2788 (Oliva) images, respectively. Experimental results and comparisons show that the proposed CBIR system performs efficiently in image retrieval field.

Keywords

RT KLD LS-SVM CBIR MGA GGD 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Manish Chowdhury
    • 1
  • Sudeb Das
    • 1
  • Malay K. Kundu
    • 1
  1. 1.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia

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