Paper
20 May 2011 Evaluation of potential emission spectra for the reliable classification of fluorescently coded materials
Siegfried Brunner, Christian Kargel
Author Affiliations +
Abstract
The conservation and efficient use of natural and especially strategic resources like oil and water have become global issues, which increasingly initiate environmental and political activities for comprehensive recycling programs. To effectively reutilize oil-based materials necessary in many industrial fields (e.g. chemical and pharmaceutical industry, automotive, packaging), appropriate methods for a fast and highly reliable automated material identification are required. One non-contacting, color- and shape-independent new technique that eliminates the shortcomings of existing methods is to label materials like plastics with certain combinations of fluorescent markers ("optical codes", "optical fingerprints") incorporated during manufacture. Since time-resolved measurements are complex (and expensive), fluorescent markers must be designed that possess unique spectral signatures. The number of identifiable materials increases with the number of fluorescent markers that can be reliably distinguished within the limited wavelength band available. In this article we shall investigate the reliable detection and classification of fluorescent markers with specific fluorescence emission spectra. These simulated spectra are modeled based on realistic fluorescence spectra acquired from material samples using a modern VNIR spectral imaging system. In order to maximize the number of materials that can be reliably identified, we evaluate the performance of 8 classification algorithms based on different spectral similarity measures. The results help guide the design of appropriate fluorescent markers, optical sensors and the overall measurement system.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Siegfried Brunner and Christian Kargel "Evaluation of potential emission spectra for the reliable classification of fluorescently coded materials", Proc. SPIE 8048, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII, 80480I (20 May 2011); https://doi.org/10.1117/12.884001
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Cited by 5 scholarly publications.
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KEYWORDS
Signal to noise ratio

Luminescence

Binary data

Surface conduction electron emitter displays

Signal detection

Fluorescent markers

Interference (communication)

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