On-Line Defect Detecting Method Based on Kernel Method

Abstract:

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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.

Info:

Periodical:

Key Engineering Materials (Volumes 474-476)

Edited by:

Garry Zhu

Pages:

858-863

DOI:

10.4028/www.scientific.net/KEM.474-476.858

Citation:

K. J. Xu et al., "On-Line Defect Detecting Method Based on Kernel Method", Key Engineering Materials, Vols. 474-476, pp. 858-863, 2011

Online since:

April 2011

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Price:

$35.00

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