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1 November 1999 Investigation of image feature extraction by a genetic algorithm
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Abstract
We describe the implementation and performance of a genetic algorithm 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-photography 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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven P. Brumby, James P. Theiler, Simon J. Perkins, Neal R. Harvey, John J. Szymanski, Jeffrey J. Bloch, and Melanie Mitchell "Investigation of image feature extraction by a genetic algorithm", Proc. SPIE 3812, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II, (1 November 1999); https://doi.org/10.1117/12.367697
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