Automatic mineral identification using genetic programming

被引：39

作者：

Ross, BJ ^{[1
]}

Fueten, F

Yashkir, DY

机构：

[1] Brock Univ, Dept Comp Sci, St Catharines, ON L2S 3A1, Canada

[2] Brock Univ, Dept Earth Sci, St Catharines, ON L2S 3A1, Canada

来源：

MACHINE VISION AND APPLICATIONS | 2001年 / 13卷 / 02期

关键词：

mineral classification; genetic programming; feature space thresholding;

D O I：

10.1007/PL00013273

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：61 / 69

页数：9

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