Wavelet- and entropy-based feature extraction: application to distinguishing mixtures of beverages

Munevver Kokuer; Fionn D. Murtagh; Andreas T. Augousti; Julian Mason; Norman Douglas McMillan

doi:10.1117/12.463733

19 March 2003 Wavelet- and entropy-based feature extraction: application to distinguishing mixtures of beverages

Munevver Kokuer, Fionn D. Murtagh, Andreas T. Augousti, Julian Mason, Norman Douglas McMillan

Proceedings Volume 4877, Opto-Ireland 2002: Optical Metrology, Imaging, and Machine Vision; (2003) https://doi.org/10.1117/12.463733
Event: OPTO Ireland, 2002, Galway, Ireland

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. (1992, 1998, 2000).

Citation Download Citation

Munevver Kokuer, Fionn D. Murtagh, Andreas T. Augousti, Julian Mason, and Norman Douglas McMillan "Wavelet- and entropy-based feature extraction: application to distinguishing mixtures of beverages", Proc. SPIE 4877, Opto-Ireland 2002: Optical Metrology, Imaging, and Machine Vision, (19 March 2003); https://doi.org/10.1117/12.463733

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