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Improvement of single wavelength-based Thai jasmine rice identification with elliptic Fourier descriptor and neural network analysis
Author(s)
Date Issued
December 1, 2012
Type
Conference 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. © Copyright SPIE.
Citation
Proceedings of SPIE the International Society for Optical Engineering, 8558, 2012