Skip to main content
Log in

Automatic mineral identification using genetic programming

  • Original papers
  • Published:
Machine Vision and Applications Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Author information

Authors and Affiliations

Authors

Additional information

Received: 18 October 1999 / Accepted: 20 January 2001

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ross, B., Fueten, F. & Yashkir, D. Automatic mineral identification using genetic programming. Machine Vision and Applications 13, 61–69 (2001). https://doi.org/10.1007/PL00013273

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/PL00013273

Navigation