Title: Beef and horse meat discrimination and storage time classification using a portable device based on DSP and PCA method

Authors: Assia Arsalane; Noureddine El Barbri; Karim Rhofir; Abdelmoumen Tabyaoui; Abdessamad Klilou

Addresses: Laboratory of Radiation, Material and Instrumentation, Sciences and Techniques Faculty, University of Hassan 1, Settat, Morocco ' Laboratory of Electrical Department, Electronic Signals and Systems Team, ENSA, University of Hassan 1, Khouribga, Morocco ' Laboratory of Electrical Department, Electronic Signals and Systems Team, ENSA, University of Hassan 1, Khouribga, Morocco ' Laboratory of Radiation, Material and Instrumentation, Sciences and Techniques Faculty, University of Hassan 1, Settat, Morocco ' LGECOS Lab, ENSA-Marrakech, University of Cadi Ayyad, Marrakech, Morocco

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.

DOI: 10.1504/IJIE.2017.087005

International Journal of Intelligent Enterprise, 2017 Vol.4 No.1/2, pp.58 - 75

Received: 24 Nov 2016
Accepted: 20 Dec 2016
Published online: 04 Oct 2017 *

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