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Self-Learning System For Surface Failure Detection (CROSBI ID 543453)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Rimac-Drlje, Snježana ; Keller, Alen ; Nyarko, Emmanuel Karlo Self-Learning System For Surface Failure Detection // Proceedings of EURASIP 13th European Signal Processing Conference EUSIPCO 2005 / Sankur, Bulent (ur.). Antalya: Bogazici University, 2005

Podaci o odgovornosti

Rimac-Drlje, Snježana ; Keller, Alen ; Nyarko, Emmanuel Karlo

engleski

Self-Learning System For Surface Failure Detection

In this article we present a self-learning system for automatic detection of surface failures on ceramic tiles. This system is based on the probabilistic neural network with radial basis. The discrete wavelet transform (DWT) is used as a preprocessing method with good feature extraction possibilities. With an automatic procedure for the production of input vectors for the neural networks training the presented system can adapt itself to different textures. Experimental results of the defect detection for different types of tiles show a high accuracy and applicability of the proposed procedure.

Surface failure detection; neural networks; wavelets; self-learning system

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Podaci o prilogu

2005.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of EURASIP 13th European Signal Processing Conference EUSIPCO 2005

Sankur, Bulent

Antalya: Bogazici University

975-00188-0-X

Podaci o skupu

13th European Signal Processing Conference EUSIPCO 2005

poster

04.09.2005-08.09.2005

Antalya, Turska

Povezanost rada

Elektrotehnika, Računarstvo

Poveznice