Marshall, Stephen and Kelman, Timothy and Qiao, Tong and Murray, Paul and Zabalza, Jaime (2015) Hyperspectral imaging for food applications. In: 23rd European Signal Processing Conference, 2015 (EUSIPCO 2015), 2015-08-31 - 2015-09-04.
Marshall_etal_EUSIPCO2015_hyperspectral_imaging_food_applications.pdf - Accepted Author Manuscript
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Food quality analysis is a key area where reliable, nondestructive and accurate measures are required. Hyperspectral imaging is a technology which meets all of these requirements but only if appropriate signal processing techniques are implemented. In this paper, a discussion of some of these state-of-the-art processing techniques is followed by an explanation of four different applications of hyperspectral imaging for food quality analysis: shelf life estimation of baked sponges; beef quality prediction; classification of Chinese tea leaves; and classification of rice grains. The first two of these topics investigate the use of hyperspectral imaging to produce an objective measure about the quality of the food sample. The final two studies are classification problems, where an unknown sample is assigned to one of a previously defined set of classes.
|Item type:||Conference or Workshop Item (Paper)|
|Notes:||© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.|
|Keywords:||signal processing, image processing, image classification, spectral imaging, hyperspectral imaging, food safety, feature extraction, covariance matrices, Electrical engineering. Electronics Nuclear engineering, Home economics, Electrical and Electronic Engineering, Food Science|
|Subjects:||Technology > Electrical engineering. Electronics Nuclear engineering
Technology > Home economics
|Department:||Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset Management
|Depositing user:||Pure Administrator|
|Date Deposited:||31 Mar 2016 14:40|
|Last modified:||21 Apr 2017 20:13|