The University of Southampton
University of Southampton Institutional Repository

New raw material discrimination system based on a spatial optical spectroscopy technique

New raw material discrimination system based on a spatial optical spectroscopy technique
New raw material discrimination system based on a spatial optical spectroscopy technique
A non-intrusive and non-contact system for real-time detection of spurious elements in raw material processing chains for industrial environments is presented. Observation line spectrographs, based on the visible.near infrared (Vis.NIR) reflectance of the material under study, are obtained using a dual spatial-spectroscopic imaging technique. To attain a representative spectral fingerprint, the large amount of data is compressed using a principal component analysis (PCA) fast algorithm prior to the classification made by a neural network. The technique has been successfully tested on the tobacco industry. However, the technique is not limited to tobacco leaves, but other materials can be discriminated or classified instead.
optical system, non-contact, imaging spectroscopy, neural networks, material classification
0924-4247
605-612
García-Allende, P.B.
b48e1be3-30b3-47e0-a917-3068c773479c
Conde, O.M.
0ec97d1c-778e-487a-b486-3bae32a4bf44
Cubillas, A.M.
333991f8-a83a-4edf-a79a-38ce16a29450
Jáuregui, C.
1fc691e2-b7a2-4344-9f6d-dbc478499e3a
López-Higuera, J.M.
acf3b7bd-9a4e-44b1-b0d9-f8d944dc30d4
García-Allende, P.B.
b48e1be3-30b3-47e0-a917-3068c773479c
Conde, O.M.
0ec97d1c-778e-487a-b486-3bae32a4bf44
Cubillas, A.M.
333991f8-a83a-4edf-a79a-38ce16a29450
Jáuregui, C.
1fc691e2-b7a2-4344-9f6d-dbc478499e3a
López-Higuera, J.M.
acf3b7bd-9a4e-44b1-b0d9-f8d944dc30d4

García-Allende, P.B., Conde, O.M., Cubillas, A.M., Jáuregui, C. and López-Higuera, J.M. (2007) New raw material discrimination system based on a spatial optical spectroscopy technique. Sensors and Actuators A: Physical, 135 (2), 605-612. (doi:10.1016/j.sna.2006.08.024).

Record type: Article

Abstract

A non-intrusive and non-contact system for real-time detection of spurious elements in raw material processing chains for industrial environments is presented. Observation line spectrographs, based on the visible.near infrared (Vis.NIR) reflectance of the material under study, are obtained using a dual spatial-spectroscopic imaging technique. To attain a representative spectral fingerprint, the large amount of data is compressed using a principal component analysis (PCA) fast algorithm prior to the classification made by a neural network. The technique has been successfully tested on the tobacco industry. However, the technique is not limited to tobacco leaves, but other materials can be discriminated or classified instead.

This record has no associated files available for download.

More information

Published date: 15 April 2007
Keywords: optical system, non-contact, imaging spectroscopy, neural networks, material classification

Identifiers

Local EPrints ID: 49792
URI: http://eprints.soton.ac.uk/id/eprint/49792
ISSN: 0924-4247
PURE UUID: 0e20018d-6497-4b76-835a-32364e645718

Catalogue record

Date deposited: 03 Dec 2007
Last modified: 08 Jan 2022 01:10

Export record

Altmetrics

Contributors

Author: P.B. García-Allende
Author: O.M. Conde
Author: A.M. Cubillas
Author: C. Jáuregui
Author: J.M. López-Higuera

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×