Optimal dimension reduction for image retrieval with correlation metrics

  • Authors:
  • Yuhua Zhu;Washington Mio;Xiuwen Liu

  • Affiliations:
  • Department of Computer Science, Florida State University;Department of Mathematics, Florida State University;Department of Computer Science, Florida State University

  • Venue:
  • IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
  • Year:
  • 2009

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Abstract

We investigate content-based image retrieval employing a representation of images based on the statistics of their spectral components and a new linear dimension reduction technique. This linear dimension reduction technique is designed to optimize class separation with respect to metrics derived from cross-correlation of spectral histograms. Our approach to retrieval involves a preliminary classification step to index images in a database followed by a class-by-class retrieval step. We carry out several experiments with the Corel database and compare the outcome with several results previously reported in the literature.