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Proceedings Paper

Based on the TF fast clustering algorithm steel surface defect feature extraction and classification
Author(s): Zhiwei Yu; Mudi Xiong; Zhuqing Niu
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Paper Abstract

To detect steel plate surface defect and collect the defect feature, this paper puts forward a steel plate surface defect detection method based on TF fast clustering algorithm, which runs fast and timely in the field of industrial fields, such as shipyard. According to the gray characteristics and geometrical characteristics, several common defects are divided into simple classifications.

Paper Details

Date Published: 26 October 2013
PDF: 6 pages
Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 89212C (26 October 2013); doi: 10.1117/12.2031817
Show Author Affiliations
Zhiwei Yu, Dalian Maritime Univ. (China)
Mudi Xiong, DaLian Maritime University (China)
Zhuqing Niu, DaLian Maritime University (China)


Published in SPIE Proceedings Vol. 8921:
MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Jinwen Tian; Jie Ma, Editor(s)

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