An efficient image pattern recognition system using an evolutionary search strategy
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Guo:2009:SMC,
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author = "Pei-Fang Guo and Prabir Bhattacharya and
Nawwaf Kharma",
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title = "An efficient image pattern recognition system using an
evolutionary search strategy",
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booktitle = "IEEE International Conference on Systems, Man and
Cybernetics, SMC 2009",
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year = "2009",
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month = oct,
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pages = "599--604",
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address = "San Antonio, Texas, USA",
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming, EM, GP,
Gaussian mixture estimation, HROIT, OPMD disease
diagnosis, efficiency 90.20 percent, evolutionary
genetic programming, evolutionary search strategy,
expectation maximization algorithm, feature function
generation, histogram region, image pattern recognition
system, image thresholding, oculopharyngeal muscular
dystrophy, primitive texture feature extraction,
support vector machine, Gaussian processes, diseases,
expectation-maximisation algorithm, eye, feature
extraction, image recognition, image segmentation,
image texture, medical image processing, muscle, search
problems",
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ISSN = "1062-922X",
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DOI = "doi:10.1109/ICSMC.2009.5346614",
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size = "6 pages",
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abstract = "A mechanism involving evolutionary genetic programming
(GP) and the expectation maximization algorithm (EM) is
proposed to generate feature functions automatically,
based on the primitive features, for an image pattern
recognition system on the diagnosis of the disease
OPMD. Prior to the feature function generation, we
introduce a novel technique of the primitive texture
feature extraction, which deals with non-uniform
images, from the histogram region of interest by
thresholds (HROIT). Compared with the performance
achieved by support vector machine (SVM) using the
whole primitive texture features, the GP-EM
methodology, as a whole, achieves a better performance
of 90.20percent recognition rate on diagnosis, while
projecting the hyperspace of the primitive features
onto the space of a single generated feature.",
-
notes = "Also known as \cite{5346614}",
- }
Genetic Programming entries for
Pei Fang Guo
Prabir Bhattacharya
Nawwaf Kharma
Citations