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Proceedings Paper

Research on on-line grading system for pearl defect based on machine vision
Author(s): Jilin Zhou; Li Ma
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Paper Abstract

A novel method for automated defect detection of pearls based on machine vision is proposed. Firstly, a dome-shaped light source with diffused light illumination was designed to improve image quality and reduce light-spot size. And a novel quasi-synchronous multi-images grabbing scheme from different views is then designed based on pearl' free-falling motion. Then a nonlinear filter based on space geometry is given to enhance defect contrasts following by a region-grow method for extracting all suspicious defects, including highlight-halation regions. Furthermore, the highlight-halation regions were removed using morphological method based on the spatial distributive model of the highlight-halation. At last, shape and texture features of defect regions are extracted and SVM method was used for defect grading. Experiments show that the acquired images included the complete information of pearl surfaces and the system correctness was over 93.3% .

Paper Details

Date Published: 29 November 2007
PDF: 7 pages
Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 68332E (29 November 2007); doi: 10.1117/12.755827
Show Author Affiliations
Jilin Zhou, Hangzhou Dianzi Univ. (China)
Li Ma, Hangzhou Dianzi Univ. (China)

Published in SPIE Proceedings Vol. 6833:
Electronic Imaging and Multimedia Technology V
Liwei Zhou; Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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