Investigation of image feature extraction by a genetic algorithm

被引：47

作者：

Brumby, SP ^{[1
]}

Theiler, J ^{[1
]}

Perkins, SJ ^{[1
]}

Harvey, N ^{[1
]}

Szymanski, JJ ^{[1
]}

Bloch, JJ ^{[1
]}

Mitchell, M ^{[1
]}

机构：

[1] Los Alamos Natl Lab, Los Alamos, NM 87545 USA

来源：

APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION II | 1999年 / 3812卷

关键词：

evolutionary computation; genetic algorithms; image analysis; multi-spectral analysis;

D O I：

10.1117/12.367697

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We describe the implementation and performance of a genetic algorithm (GA) which generates image feature extraction algorithms for remote sensing applications. We describe our basis set of primitive image operators and present our chromosomal representation of a complete algorithm. Our initial application has been geospatial feature extraction using publicly available multi-spectral aerial-photogaphy data sets. We present the preliminary results of our analysis of the efficiency of the classic genetic operations of crossover and mutation for our application, and discuss our choice of evolutionary control parameters. We exhibit some of our evolved algorithms, and discuss possible avenues for future progress.

引用

页码：24 / 31

页数：8

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