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16 September 2002 New approach to classification of surface defects in steel plate based on fuzzy neural networks
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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.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kangsheng Lai, Haidong Zhang, and Dongming Dai "New approach to classification of surface defects in steel plate based on fuzzy neural networks", Proc. SPIE 4929, Optical Information Processing Technology, (16 September 2002); https://doi.org/10.1117/12.483251
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