Image classification and processing using modified parallel-ACTIT

  • Authors:
  • Jun Ando;Tomoharu Nagao

  • Affiliations:
  • Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Kanagawa, Japan;Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Kanagawa, Japan

  • Venue:
  • SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
  • Year:
  • 2009

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Abstract

Image processing and recognition technologies are required to solve various problems. We have already proposed the system which automatically constructs image processing with Genetic Programming (GP), Automatic Construction of Tree-structural Image Transformation (ACTIT). However, it is necessary that training image sets are properly classified in advance if they have various characteristics. In this paper, we propose Modified Parallel-ACTIT which automatically classifies training image sets into several subpopulations. And it optimizes tree-structural image transformation for each training image sets in each subpopulations. We show experimentally that Modified Parallel-ACTIT is more effective in comparison with ordinary ACTIT.