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
收藏
页码：61 / 69
页数：9
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