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Shape Description for Content-Based Image Retrieval

  • E. Ardizzone
  • A. Chella
  • R. Pirrone
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)

Abstract

The present work is focused on a global image characterization based on a description of the 2D displacements of the different shapes present in the image, which can be employed for CBIR applications. To this aim, a recognition system has been developed, that detects automatically image ROIs containing single objects, and classiffies them as belonging to a particular class of shapes. In our approach we make use of the eigenvalues of the covariance matrix computed from the pixel rows of a single ROI. These quantities are arranged in a vector form, and are classiffed using Support Vector Machines (SVMs). The selected feature allows us to recognize shapes in a robust fashion, despite rotations or scaling, and, to some extent, independently from the light conditions. Theoretical foundations of the approach are presented in the paper, together with an outline of the system, and some preliminary experimental results.

Keywords

Image Indexing Cumulative Function Video Database Optimal Hyperplane Shape Class 
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

  • E. Ardizzone
    • 1
    • 2
  • A. Chella
    • 1
    • 2
  • R. Pirrone
    • 1
    • 2
  1. 1.DIAI - University of PalermoItaly
  2. 2.CERE - National Research CouncilItaly

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