Paper
29 November 2007 Research on on-line grading system for pearl defect based on machine vision
Jilin Zhou, Li Ma
Author Affiliations +
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% .
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jilin Zhou and Li Ma "Research on on-line grading system for pearl defect based on machine vision", Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 68332E (29 November 2007); https://doi.org/10.1117/12.755827
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Cited by 2 scholarly publications.
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KEYWORDS
Image enhancement

Image segmentation

Cameras

Defect detection

Feature extraction

Machine vision

Light sources

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