Taking Fuzzy-Rough Application to Mars

Fuzzy-Rough Feature Selection for Mars Terrain Image Classification
  • Changjing Shang
  • Dave Barnes
  • Qiang Shen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5908)


This paper presents a novel application of fuzzy-rough set-based feature selection (FRFS) for Mars terrain image classification. The work allows the induction of low-dimensionality feature sets from sample descriptions of feature patterns of a much higher dimensionality. In particular, FRFS is applied in conjunction with multi-layer perceptron and K-nearest neighbor based classifiers. Supported with comparative studies, the paper demonstrates that FRFS helps to enhance the effectiveness and efficiency of conventional classification systems, by minimizing redundant and noisy features. This is of particular significance for on-board image classification in future Mars rover missions.


Feature Selection Hide Node Feature Selection Technique Mars Exploration Rover Panoramic Camera 
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 2009

Authors and Affiliations

  • Changjing Shang
    • 1
  • Dave Barnes
    • 1
  • Qiang Shen
    • 1
  1. 1.Dept. of Computer ScienceAberystwyth UniversityWalesUK

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