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Machine Vision and Applications

, Volume 13, Issue 2, pp 61–69 | Cite as

Automatic mineral identification using genetic programming

  • B.J. Ross
  • F. Fueten
  • D.Y. Yashkir
Original papers

Abstract.

Automatic mineral identification using evolutionary computation technology is discussed. Thin sections of mineral samples are photographed digitally using a computer-controlled rotating polarizer stage on a petrographic microscope. A suite of image processing functions is applied to the images. Filtered image data for identified mineral grains is then selected for use as training data for a genetic programming system, which automatically synthesizes computer programs that identify these grains. The evolved programs use a decision-tree structure that compares the mineral image values with one other, resulting in a thresholding analysis of the multi-dimensional colour and textural space of the mineral images.

Key words: Mineral classification – Genetic programming – Feature space thresholding 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • B.J. Ross
    • 1
  • F. Fueten
    • 2
  • D.Y. Yashkir
    • 1
  1. 1.Department of Computer Science, Brock University, St. Catharines, Ontario L2S 3A1, Canada; e-mail: bross@cosc.brocku.ca CA
  2. 2.Department of Earth Sciences, Brock University, St. Catharines, Ontario L2S 3A1, Canada CA

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