Wavelet-Based Salient Points: Applications to Image Retrieval Using Color and Texture Features

  • Etienne Loupias
  • Nicu Sebe
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)


In image retrieval, global features related to color or texture are commonly used to describe the image. The use of interest points in contentbased image retrieval allows image index to represent local properties of images. Classic corner detectors can be used for this purpose. However, they have drawbacks when applied to various natural images for image retrieval, because visual features need not to be corners and corners may gather in small regions. We present a salient point detector that extracts points where variations occur in the image, regardless whether they are corner-like or not. It is based on wavelet transform to detect global variations as well as local ones. We show that extracting the color information in the locations given by these points provides significantly improved retrieval results as compared to the global color feature approach. We also show an image retrieval experiment based on texture features where our detector provides better retrieval performance comparing with other point detectors.


Image Retrieval Wavelet Coefficient Interest Point Natural Image Salient Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Etienne Loupias
    • 1
  • Nicu Sebe
    • 2
  1. 1.Laboratoire Reconnaissance de Formes et VisionFrance
  2. 2.Leiden Institute of AdvancedComputer ScienceLeiden UniversityThe Netherlands

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