Beef and horse meat discrimination and storage time classification using a portable device based on DSP and PCA method
Assia Arsalane,
Noureddine El Barbri,
Karim Rhofir,
Abdelmoumen Tabyaoui and
Abdessamad Klilou
International Journal of Intelligent Enterprise, 2017, vol. 4, issue 1/2, 58-75
Abstract:
Food authenticity is an issue of major concern. The adulteration of meat products with horse meat drew attention to the development of robust techniques for meat species classification. This work presents an instrument and a method to discriminate among horse and beef meat and to classify their degree of spoilage based on meat colour. The proposed device employs charge-coupled device (CCD) imaging techniques, digital image processing, digital signal processor (DSP), processing techniques and liquid crystal display (LCD) screen. Samples were placed under cold storage at 4°C for two weeks. Two colour models are used to define beef and horse meat: red, green, and blue (RGB) and hue, saturation and intensity (HSI). Principal component analysis (PCA) was employed to optimise the data matrix. Results show that the device was able to distinguish between beef and horse meat and to classify them according to the number of days spent in cold storage.
Keywords: meat discrimination; digital signal processor; DSP; portable instrument; embedded system. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=87005 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijient:v:4:y:2017:i:1/2:p:58-75
Access Statistics for this article
More articles in International Journal of Intelligent Enterprise from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().