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Bibliographic record number: 372374


Authors: Rimac-Drlje, Snježana; Keller, Alen; Nyarko, Emmanuel Karlo
Title: Self-Learning System For Surface Failure Detection
Source: Proceedings of EURASIP 13th European Signal Processing Conference EUSIPCO 2005 / Sankur, Bulent (ed). - Antalya : Bogazici university Printhouse , 2005. (ISBN: 975-00188-0-X).
Meeting: 13th European Signal Processing Conference EUSIPCO 2005
Location and date: Antalya, Turska, 4-8.09.2005.
Keywords: Surface failure detection; neural networks; wavelets; self-learning system
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.
Type of meeting: Poster
Type of presentation in a journal: Full-text (1500 words and more)
Type of peer-review: International peer-review
Project / theme: 0165103
Original language: ENG
Category: Znanstveni
Research fields:
Electrical engineering,Computer science
Contrib. to CROSBI by: (, 20. Stu. 2008. u 09:55 sati

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