• DocumentCode
    2215384
  • Title

    A domain independent Genetic Programming approach to automatic feature extraction for image classification

  • Author

    Atkins, Daniel ; Neshatian, Kourosh ; Zhang, Mengjie

  • Author_Institution
    Sch. of Eng. & Comput. Sci., Victoria Univ. of Wellington, Wellington, New Zealand
  • fYear
    2011
  • fDate
    5-8 June 2011
  • Firstpage
    238
  • Lastpage
    245
  • Abstract
    In this paper we explore the application of Genetic Programming (GP) to the problem of domain-independent image feature extraction and classification. We propose a new GP based image classification system that extracts image features autonomously, and compare its performance against a baseline GP-based classifier system that uses human-extracted features. We found that the proposed system has a similar performance to the baseline system, and that GP is capable of evolving a single program that can both extract useful features and use those features to classify an image.
  • Keywords
    feature extraction; genetic algorithms; image classification; automatic image feature extraction; baseline system; classifier system; domain independent genetic programming; human-extracted features; image classification; Accuracy; Feature extraction; Filtering; Genetic programming; Humans; Object detection; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2011 IEEE Congress on
  • Conference_Location
    New Orleans, LA
  • ISSN
    Pending
  • Print_ISBN
    978-1-4244-7834-7
  • Type

    conf

  • DOI
    10.1109/CEC.2011.5949624
  • Filename
    5949624