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Proceedings Paper

Improvement of single wavelength-based Thai jasmine rice identification with elliptic Fourier descriptor and neural network analysis
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Paper Abstract

Instead of considering only the amount of fluorescent signal spatially distributed on the image of milled rice grains this paper shows how our single-wavelength spectral-imaging-based Thai jasmine (KDML105) rice identification system can be improved by analyzing the shape and size of the image of each milled rice variety especially during the image threshold operation. The image of each milled rice variety is expressed as chain codes and elliptic Fourier coefficients. After that, a feed-forward back-propagation neural network model is applied, resulting in an improved average FAR of 11.0% and FRR of 19.0% in identifying KDML105 milled rice from the unwanted four milled rice varieties.

Paper Details

Date Published: 30 November 2012
PDF: 10 pages
Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85580C (30 November 2012); doi: 10.1117/12.999852
Show Author Affiliations
Kajpanya Suwansukho, King Mongkut's Institute of Technology Ladkrabang (Thailand)
Sarun Sumriddetchkajorn, National Science and Technology Development Agency (Thailand)
Prathan Buranasiri, King Mongkut's Institute of Technology Ladkrabang (Thailand)


Published in SPIE Proceedings Vol. 8558:
Optoelectronic Imaging and Multimedia Technology II
Tsutomu Shimura; Guangyu Xu; Linmi Tao; Jesse Zheng, Editor(s)

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