On-Line Defect Detecting Method Based on Kernel Method

The conflict between accuracy and speed is one of the most well-known dilemmas of the real-time defect detecting system. This paper presents a real-time defect detecting algorithm based on Kernel principal component analysis (KPCA). KPCA-based feature extraction have recently shown to be very effect...

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Bibliographic Details
Published in:Key engineering materials 2011-01, Vol.474-476 (SUPPL.2), p.858-863
Main Authors: Chen, Bin, Xu, Ke Jia, Zeng, Li
Format: Article
Language:English
Subjects:
Algorithms
Defects
Feature extraction
Kernels
On-line systems
Principal component analysis
Real time
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Summary:The conflict between accuracy and speed is one of the most well-known dilemmas of the real-time defect detecting system. This paper presents a real-time defect detecting algorithm based on Kernel principal component analysis (KPCA). KPCA-based feature extraction have recently shown to be very effective for image denoising, however the Normal KPCA method is time-consuming. In our method, we propose a progressive algorithm to speed up the reconstruct process while improve accuracy. Experimental results demonstrate that our method is dramatically better than Normal KPCA Pre-image method in terms of speed and performance.
ISSN:1013-9826
1662-9795
1662-9795
DOI:10.4028/www.scientific.net/KEM.474-476.858