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Proceedings Paper

Single-wavelength based Thai jasmine rice identification with polynomial fitting function and neural network analysis
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Paper Abstract

We previously showed that a combination of image thresholding, chain coding, elliptic Fourier descriptors, and artificial neural network analysis provided a low false acceptance rate (FAR) and a false rejection rate (FRR) of 11.0% and 19.0%, respectively, in identify Thai jasmine rice from three unwanted rice varieties. In this work, we highlight that only a polynomial function fitting on the determined chain code and the neural network analysis are highly sufficient in obtaining a very low FAR of < 3.0% and a very low 0.3% FRR for the separation of Thai jasmine rice from Chainat 1 (CNT1), Prathumtani 1 (PTT1), and Hom-Pitsanulok (HPSL) rice varieties. With this proposed approach, the analytical time is tremendously suppressed from 4,250 seconds down to 2 seconds, implying extremely high potential in practical deployment.

Paper Details

Date Published: 7 June 2013
PDF: 8 pages
Proc. SPIE 8883, ICPS 2013: International Conference on Photonics Solutions, 888318 (7 June 2013); doi: 10.1117/12.2021861
Show Author Affiliations
Kajpanya Suwansukho, King Mongkut's Institute of Technology Ladkrabang (Thailand)
Sarun Sumriddetchkajorn, National Electronics and Computer Technology Ctr. (Thailand)
Prathan Buranasiri, King Mongkut's Institute of Technology Ladkrabang (Thailand)

Published in SPIE Proceedings Vol. 8883:
ICPS 2013: International Conference on Photonics Solutions
Prathan Buranasiri; Sarun Sumriddetchkajorn, Editor(s)

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