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Self-Learning System For Surface Failure Detection


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 Printhouse, 2005. (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Self-Learning System For Surface Failure Detection

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

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of EURASIP 13th European Signal Processing Conference EUSIPCO 2005 / Sankur, Bulent - Antalya : Bogazici university Printhouse, 2005

ISBN
975-00188-0-X

Skup
13th European Signal Processing Conference EUSIPCO 2005

Mjesto i datum
Antalya, Turska, 4-8.09.2005

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

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

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo



POVEZANOST RADA


Projekt / tema
0165103

Ustanove
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek