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Sensors 2015, 15(1), 611-634; doi:10.3390/s150100611

Analysis of Discrimination Techniques for Low-Cost Narrow-Band Spectrofluorometers

1
Physical and Technological Oceanography Department, Institute of Marine Sciences (ICM-CSIC), Pg. Marítim de la Barceloneta, 37-49, Barcelona 08003, Spain
2
AtlantTIC, University of Vigo (UVigo), Maxwell Street, Vigo 36310, Spain
*
Author to whom correspondence should be addressed.
Received: 7 October 2014 / Accepted: 23 December 2014 / Published: 30 December 2014
(This article belongs to the Section Physical Sensors)
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Abstract

The need for covering large areas in oceanographic measurement campaigns and the general interest in reducing the observational costs open the necessity to develop new strategies towards this objective, fundamental to deal with current and future research projects. In this respect, the development of low-cost instruments becomes a key factor, but optimal signal-processing techniques must be used to balance their measurements with those obtained from accurate but expensive instruments. In this paper, a complete signal-processing chain to process the fluorescence spectra of marine organisms for taxonomic discrimination is proposed. It has been designed to deal with noisy, narrow-band and low-resolution data obtained from low-cost sensors or instruments and to optimize its computational cost, and it consists of four separated blocks that denoise, normalize, transform and classify the samples. For each block, several techniques are tested and compared to find the best combination that optimizes the classification of the samples. The signal processing has been focused on the Chlorophyll-a fluorescence peak, since it presents the highest emission levels and it can be measured with sensors presenting poor sensitivity and signal-to-noise ratios. The whole methodology has been successfully validated by means of the fluorescence spectra emitted by five different cultures. View Full-Text
Keywords: classification; denoising; fluorescence; low-cost sensors; normalization; signal processing; taxonomic discrimination; transformation classification; denoising; fluorescence; low-cost sensors; normalization; signal processing; taxonomic discrimination; transformation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Aymerich, I.F.; Sánchez, A.-M.; Pérez, S.; Piera, J. Analysis of Discrimination Techniques for Low-Cost Narrow-Band Spectrofluorometers. Sensors 2015, 15, 611-634.

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