Publication: Automated machine vision system for inspecting cutting quality of cubic zirconia
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Issued Date
2016
Resource Type
File Type
application/pdf
ISSN
189456
Other identifier(s)
2-s2.0-84971441298
Rights Holder(s)
Scopus
Bibliographic Citation
IEEE Transactions on Instrumentation and Measurement. Vol 65, No.9 (2016), p.2078-2087
Suggested Citation
Ekwongmunkong W., Mittrapiyanuruk P., Kaewtrakulpong P. Automated machine vision system for inspecting cutting quality of cubic zirconia. IEEE Transactions on Instrumentation and Measurement. Vol 65, No.9 (2016), p.2078-2087. doi:10.1109/TIM.2016.2566858 Retrieved from: https://hdl.handle.net/20.500.14740/5191
Abstract
In this paper, we present an automated system for the visual inspection of cubic zirconia (CZ) cut quality. In particular, we inspect the cut quality from pavilion facets of the CZ. For the hardware, the system includes a computerized-control mechanical part that performs both the task of feeding the CZ to the inspection station and the task of separating the gemstone according to the inspection result. In terms of software, we propose an image processing algorithm that consists of two major steps. For the first step, pavilion facets are extracted from the CZ image acquired from the pavilion side. In particular, we resort to the idea of 1-D edge detection in conjunction with random sample consensus line fitting for the pavilion facet extraction. For the second step, a set of measures derived from the extracted facet structure are calculated and are used for cut quality judgment as either accept or reject. The metrological analysis of the system is also investigated. We perform an experiment to inspect 1756 object images consisting of both good and bad samples. The performance of our system yields to about 5.21% of false reject rate and 0% of false acceptance rate. The system can inspect CZ with a rate of 1 sample/s. © 1963-2012 IEEE.