Steven P. Brumby, James Theiler, Simon Perkins, Neal Harvey, John J. Szymanski, Jeffrey J. Bloch, and Melanie Mitchell (1999) "Investigation of Image Feature Extraction by a Genetic Algorithm", in Proceedings of SPIE 3812, pp. 24-31.  Home/Search   Document Details and Download   Summary   Related Articles   Check

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S. P. Brumby, J. Theiler, S. Perkins, N. Harvey, J. J. Szymanski, J. J. Bloch, and M. Mitchell, "Investigation of image feature extraction by a genetic algorithm," in Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II, B. Bosacchi, D. B. Fogel, and J. C. Bezdek, eds., Proc SPIE 3812, 1999.

....yet it is clear that a suitable choice of additional dimensions could make classification much easier. Unfortunately, this suitable choice is, in general, application specific. To address this problem, we have developed a hybrid evolutionaryalgorithmcalledGENeticImageryExploitation (GENIE) [2] [8] that searches through the space of image processing algorithms. GENIE is a hybrid in that the evolutionary part of the program attempts to identify a pipeline of image processing operations which transform the raw multi spectral data planes into a new set of image planes; these intermediate ....

S. P. Brumby, J. Theiler, S. J. Perkins, N. R. Harvey, J. J. Szymanski, J. J. Bloch, and M. Mitchell, "Investigation of image feature extraction by a genetic algorithm," Proc. SPIE, vol. 3812, pp. 24--31, 1999.

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S.P. Brumby, J. Theiler, S.J. Perkins, N.R. Harvey, J.J. Szymanski, J.J. Bloch and M. Mitchell, "Investigation of Image Feature Extraction by a Genetic Algorithm", in Proc. SPIE 3812 pp. 24--31 (1999).

....possible image processing algorithm. GP has previously been applied to image processing problems, including: edge detection [4] face recognition [5] image segmentation [6] image compression [7] and feature extraction in remote sensing images [8 10] The work of Daida et al. 8] Brumby et al. [9] and Theiler et al. 10] is of particular relevance since it demonstrates that GP can be employed to successfully evolve algorithms for real tasks in remote sensing applications. 2 System Overview We call our feature detection system Genie (GENetic Image Exploitation) 9, 10] Genie employs a ....

....al. 8] Brumby et al. 9] and Theiler et al. 10] is of particular relevance since it demonstrates that GP can be employed to successfully evolve algorithms for real tasks in remote sensing applications. 2 System Overview We call our feature detection system Genie (GENetic Image Exploitation) [9, 10] Genie employs a classic evolutionary paradigm: a population of individuals is maintained and each individual is assessed and assigned a fitness value. The fitness of an individual is based on an objective measure of its performance in its environment. After fitness determination, the evolutionary ....

Brumby, S.P., Theiler, J., Perkins, S.J., Harvey, N.R., Szymanski, J.J., Bloch J.J., Mitchell, M.: Investigation of Image Feature Extraction by a Genetic Algorithm. In: Proc. SPIE 3812 (1999) 24--31

....To be classified as water under this cut, a pixel must have a low radiance in the NIR, a green red ratio greater than one, and have a value less than the average of values in a surrounding kernel. Some preliminary results on the application of the GP scheme to this problem are described in Ref. [19]. 3.2. Vegetation Water is water is water (well, more or less) but vegetation can be a jungle canopy in Guatemala, a corn field in Iowa, or a lone saguaro in Tombstone, Arizona. Nonetheless, nearly all vegetation exhibits a characteristic feature in the V NIR (Visible and Near Infrared) it is ....

S. P. Brumby, J. Theiler, S. Perkins, N. Harvey, J. J. Szymanski, J. J. Bloch, and M. Mitchell, "Investigation of image feature extraction by a genetic algorithm," in Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II, B. Bosacchi, D. B. Fogel, and J. C. Bezdek, eds., Proc SPIE 3812, 1999.

....a suitable choice of features couldm ake classificationm uch easier. Unfortunately, this suitable choice is, in general, application specific. It is in order to address just this problem that we have developed a hybrid evolutionary algorithm called Genie (GENetic Im agery Exploitation) [2], 3] 4] 5] 6] 7] 8] that searches through the space of im age processing algorithm s. Genie is a hybrid in that the evolutionary part of the program attem6: to identify a pipeline of i m ge processing operations which transform the rawm ulti spectral data planes into a new set ....

.... due to the fact that each individual will represent a possible im ge processing algorithm GP has previously been applied to im ge processing problem2 including: edge detection [12] face recognition [13] im agesegm entation [14] and feature extraction inrem ote sensing im ages [15] [2], 3] The work of Daida et al. 15] Brum by et al. 2] and Theiler et al. 3] is of particular relevance since it dem43 strates that GP can beem26 yed to successfully evolve algorithm s for real tasks in rem ote sensing applications. This paper describes our system in detail together ....

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S.P. Brumby J. Theiler S.J. Perkins N.R. Harvey J.J. Szymanski J.J. Bloch M. Mitchell "Investigation of Image Feature Extraction by a Genetic Algorithm" Proc. SPIE 3812 (1999) pp. 24--31.

No context found.

S.P. Brumby, J. Theiler, S.J. Perkins, N.R. Harvey, J.J. Szymanski, J.J. Bloch and M. Mitchell, "Investigation of Image Feature Extraction by a Genetic Algorithm", in Proc. SPIE 3812 pp. 24--31 (1999).

No context found.

Brumby, S.P., J. Theiler, S.J. Perkins, N. Harvey, J.J. Szymanski, J.J. Bloch, and M. Mitchell, "Investigation of Image Feature Extraction by a Genetic Algorithm," proceedings of SPIE 3812, 24-31 (1999).

No context found.

Steven P. Brumby, James Theiler, Simon Perkins, Neal Harvey, John J. Szymanski, Jeffrey J. Bloch, and Melanie Mitchell (1999) "Investigation of Image Feature Extraction by a Genetic Algorithm", in Proceedings of SPIE 3812, pp. 24-31.

No context found.

S. Brumby, J. Theiler, S. Perkins, N. Harvey, J. Szymanski, J. Bloch, and M. Mitchell. Investigation of image feature extraction by a genetic algorithm, 1999.

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