Content-based image retrieval using wavelets

  • Authors:

  • L. Flores-Pulido;O. Starostenko;D. Flores-Quéchol;J. I. Rodrigues-Flores;Ingrid Kirschning;J. A. Chávez-Aragón

  • Affiliations:

  • Universidad Autónoma de Tlaxcala, Visual Tech. Lab., Mexico;ICT Lab., Research Center CENTIA, Universidad de las Américas-Puebla, Cholula, Puebla, Mexico;Universidad Autónoma de Tlaxcala, Visual Tech. Lab., Mexico;Universidad Autónoma de Tlaxcala, Visual Tech. Lab., Mexico;ICT Lab., Research Center CENTIA, Universidad de las Américas-Puebla, Cholula, Puebla, Mexico;Universidad Autónoma de Tlaxcala, Visual Tech. Lab., Mexico

  • Venue:
  • CEA'08 Proceedings of the 2nd WSEAS International Conference on Computer Engineering and Applications
  • Year:
  • 2008

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Abstract

This paper presents a novel approach for content-based image retrieval (CBIR) that provides the analysis of visual information using wavelet coefficients and similarity metrics. This approach has a better performance than well-known RedNew CBIR system based on image indexing and retrieval using neural networks. A principal goal of this report is precise analysis of the four families of wavelets and three techniques for computing similarity. The best Symlet transform and similarity metrics based on Euclidian distance have been adopted in a proposed system called Image Retrieval by Wavelet Coefficients IRWC. In order to test a proposed system the recall and precision metrics used for evaluating the performance of CBIR facilities have been used on base of the standard COIL-100 image collections. The obtained results show the increment of retrieval efficiency up to 92% without additional increasing a processing time. Therefore a proposed approach may be considered as a good alternative for design of new CBIR systems.