DocumentCode :
3242585
Title :
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
Link To Document :
بازگشت