Paper
7 June 2013 Single-wavelength based Thai jasmine rice identification with polynomial fitting function and neural network analysis
Author Affiliations +
Proceedings Volume 8883, ICPS 2013: International Conference on Photonics Solutions; 888318 (2013) https://doi.org/10.1117/12.2021861
Event: International Conference on Photonics Solutions 2013, 2013, Pattaya City, Thailand
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kajpanya Suwansukho, Sarun Sumriddetchkajorn, and Prathan Buranasiri "Single-wavelength based Thai jasmine rice identification with polynomial fitting function and neural network analysis", Proc. SPIE 8883, ICPS 2013: International Conference on Photonics Solutions, 888318 (7 June 2013); https://doi.org/10.1117/12.2021861
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image compression

Image processing

Image segmentation

Neural networks

Imaging systems

Analytical research

Imaging spectroscopy

RELATED CONTENT


Back to Top