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CLASSIFIER COMBINATION APPLIED FOR UNDERSTANDING OF EYES IMAGES

Associated Scientists Technological Development Ltd., Computational System Division, 1.717, Alfredo Lopes St. Sao Carlos, Zip Code 13560-460, Sao Paulo, Brazil

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ANDRE C. PONCE DE LEON F. DE CARVALHO

Institute of Mathematical and Computer Science, University of Sao Paulo, Trabalhador Sao-carlense avenue, 400 Sao Carlos, Zip Code 13560-970, Sao Paulo, Brazil

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https://doi.org/10.1142/S1469026805001672Cited by:0 (Source: Crossref)

Abstract

The article presents the development of a Classifiers Combination based on machine learning techniques (Artificial Neural Networks, Support Vector Machines and C4.5 algorithm) which were able to increase the performance achieved by the Refractive Errors Measurement System (REMS) that analyzes Hartmann-Shack (HS) images from human eyes. The HS images are analyzed in order to extract relevant data for identification of refractive errors (myopia, hypermetropia and astigmatism). Those data are extracted using Gabor wavelets transform and afterwards, machine learning techniques are employed to carry out the image analysis.

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