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Optimising the complete image feature extraction chain

  • M. Mirmehdi
  • P. L. Palmer
  • J. Kittler
Session S1B: Segmentation and Grouping
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1352)

Abstract

The hypothesis verification stage of the traditional image processing approach, consisting of low, medium, and high level processing, will suffer if the set of low level features extracted are of poor quality. We investigate the optimisation of the feature extraction chain by using Genetic Algorithms. The fitness function is a performance measure which reflects the quality of an extracted set of features. We will present some results and compare them with a Hill-Climbing approach.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • M. Mirmehdi
    • 1
  • P. L. Palmer
    • 2
  • J. Kittler
    • 2
  1. 1.Dept. of Computer ScienceUniversity of BristolBristolEngland
  2. 2.Centre for Vision, Speech and Signal ProcessingSurrey UniversityGuildfordEngland

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