Digital Imaging Based Classification and Authentication of Granular Food Products

Carter, Robert M. and Yan, Yong and Tomlins, Keith I. (2006) Digital Imaging Based Classification and Authentication of Granular Food Products. Measurement Science and Technology, 17 (2). pp. 235-240. ISSN 0957-0233. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1088/0957-0233/17/2/002

Abstract

In the food industry there are many types of product that are in the form of particles, granules or grains. Consistent material size and quality within any given sample is an important requirement that is well known in industry. In addition it is possible that samples of material may be of unknown type or have been subject to adulteration, thus making material authentication a real requirement. The present work implements an advanced, but cost-effective, digital imaging and image processing technique to characterize granular foodstuffs either in real time process control or in an off-line, sample-based, manner. The imaging approach not only provides cost-effective and rugged hardware when compared with other approaches but also allows precise characterization of individual grains of material. In this paper the imaging system is briefly described and the parameters it measures are discussed. Both cluster and discriminant analyses are performed to establish the suitability of the measured parameters for authenticity study and a simple fuzzy logic is implemented based on the findings. Tests are performed, using rice as an example, to evaluate the performance of the system for authenticity testing, and encouraging results are achieved

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA166 Instrumentation
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Yiqing Liang
Date Deposited: 05 Sep 2008 14:15
Last Modified: 18 Jun 2014 15:19
Resource URI: http://kar.kent.ac.uk/id/eprint/9718 (The current URI for this page, for reference purposes)
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