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