Paper Title:
On-Line Defect Detecting Method Based on Kernel Method
  Abstract

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, B. Chen, L. Zeng, "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
$32.00
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