DocumentCode
2611276
Title
Attributes Reduction Applied to Leather Defects Classification
Author
Amorim, Willian Paraguassu ; Pistori, H. ; Pereira, M.C. ; Jacinto, Manuel Antonio Chagas
Author_Institution
Exact Sci. Dept., UFMS, Corumba, Brazil
fYear
2010
fDate
Aug. 30 2010-Sept. 3 2010
Firstpage
353
Lastpage
359
Abstract
This paper presents a study on attributes reduction, comparing five discriminant analysis techniques: FisherFace, CLDA, DLDA, YLDA and KLDA. Attributes reduction has been applied to the problem of leather defect classification using four different classifiers: C4.5, kNN, Naïve Bayes and Support Vector Machines. The results of several experiments on the performance of discriminant analysis applied to the problem of defect detection are reported.
Keywords
Bayes methods; object detection; support vector machines; C4.5; CLDA; DLDA; FisherFace; KLDA; SVM; YLDA; attributes reduction; discriminant analysis techniques; kNN; leather defects classification; naive Bayes; support vector machines; Covariance matrix; Histograms; Pixel; Principal component analysis; Support vector machines; Testing; Training; attributes reduction; leather defect detection; linear discriminant analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Graphics, Patterns and Images (SIBGRAPI), 2010 23rd SIBGRAPI Conference on
Conference_Location
Gramado
Print_ISBN
978-1-4244-8420-1
Type
conf
DOI
10.1109/SIBGRAPI.2010.54
Filename
5720389
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