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Proceedings Paper

New approach to classification of surface defects in steel plate based on fuzzy neural networks
Author(s): Kangsheng Lai; Haidong Zhang; Dongming Dai
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Paper Abstract

An automated vision system is presented intending to detect and classify surface defects on steel strip. The framework of the system is briefly introduced and the realization, mainly focused on image processing and pattern classification, is discussed in detail. Original images of defects obtained from CCD camera are preprocessed firstly by using of DSP, which includes threshold segmentation, morphological operations, edge detection, and contour extraction. After several key features have been selected, they are inputted into fuzzy neural network functioned as classifier. The result shows that the fuzzy neural network classifier provides better classification accuracy and lower iteration times.

Paper Details

Date Published: 16 September 2002
PDF: 10 pages
Proc. SPIE 4929, Optical Information Processing Technology, (16 September 2002); doi: 10.1117/12.483251
Show Author Affiliations
Kangsheng Lai, Dalian Univ. of Technology (China)
Haidong Zhang, Dalian Univ. of Technology (China)
Dongming Dai, Dalian Univ. of Technology (China)

Published in SPIE Proceedings Vol. 4929:
Optical Information Processing Technology
Guoguang Mu; Francis T. S. Yu; Suganda Jutamulia, Editor(s)

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