Classification of bidimensional images using artificial intelligence techniques

Author

Perelmuter, Guy ; Pereira, Paulo C Amaral ; Vellasco, Marley ; Pacheco, Marco Aurélio ; Carrera, Enrique V.

Author_Institution

Dept. de Engenharia Eletrica, Pontificia Univ. Catolica do Rio de Janeiro, Brazil

fYear

1996

fDate

9-11 Dec 1996

Firstpage

39

Lastpage

44

Abstract

This article presents the structure of an “intelligent classifier” composed of three modules: 1) the preprocessor, responsible for the transformation of the raw image; 2) the characteristics extractor, implemented by a genetic algorithm, which is responsible for the selection of the most relevant coefficients; and 3) the classifier, implemented by a neural network. Generic algorithms have been used as a search technique for large sets of data and neural networks, due to their ability to extract information from complex sets of data, have been largely applied in computer vision for pattern classification. The complete image classification system is invariant to translation rotation and sizing of the analysed object

Keywords

backpropagation; computer vision; feature extraction; genetic algorithms; image classification; neural nets; artificial intelligence; backpropagation; bidimensional images; characteristics extractor; computer vision; genetic algorithm; intelligent image classifier; neural network; preprocessor; Artificial intelligence; Artificial neural networks; Competitive intelligence; Computer networks; Data mining; Genetic algorithms; Image analysis; Independent component analysis; Machine vision; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetic Vision, 1996. Proceedings., Second Workshop on

Conference_Location

Sao Carlos

Print_ISBN

0-8186-8058-X

Type

conf

DOI

10.1109/CYBVIS.1996.629437

Filename

629437