Wavelet- and Entropy-Based Feature Extraction: Application to Distinguishing Mixtures of Beverages

Münevver Köküer, Fionn Murtagh, Andy T. Augousti, Julian Mason, Norman D. McMillan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The work which we report on here makes use of a new (patented) technique for measuring the tensile and viscosity properties of any liquid. One modality uses a laser-derived beam of light directed into a drop as it builds up on a drop-head, grows and eventually falls off through gravity. The light is reflected through the drop, and a trace is built up of its intensity over time. The trace has been found to have very good discrimination potential for various classes of liquid. Other sensing modalities can be used, - multiple simultaneous optical and near infrared wavelengths, ultraviolet, ultrasound. In the studies reported on here, we use the ultrasound modality. Further background on this new technology for the fingerprinting of liquid content and composition can be found in McMillan et al.

Original languageEnglish
Title of host publicationOpto-Ireland 2002
Subtitle of host publicationOptical Metrology, Imaging, and Machine Vision
EditorsAndrew Shearer, Fionn D. Murtagh, James Mahon, Paul F. Whelan
PublisherSPIE
Pages175-182
Number of pages8
Volume4877
ISBN (Print)0819446580, 9780819446589
DOIs
Publication statusPublished - 19 Mar 2003
Externally publishedYes
EventOpto-Ireland 2002: Optical metrology, Imaging, and Machine Vision - Galway, Ireland
Duration: 5 Sep 20026 Sep 2002
https://www.researchgate.net/publication/260899755_Opto-Ireland_2002_Optical_Metrology_Imaging_and_Machine_Vision

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
PublisherSPIE
Volume4877
ISSN (Print)0277-786X

Conference

ConferenceOpto-Ireland 2002: Optical metrology, Imaging, and Machine Vision
Country/TerritoryIreland
CityGalway
Period5/09/026/09/02
Internet address

Fingerprint

Dive into the research topics of 'Wavelet- and Entropy-Based Feature Extraction: Application to Distinguishing Mixtures of Beverages'. Together they form a unique fingerprint.

Cite this