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Proceedings Paper

Comparison of classification techniques for the identification of Australian wheat varieties
Author(s): Douglas Graham Myers; Timo A. Vuori
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Paper Abstract

Pattern recognition techniques have some attraction for the automatic identification of seeds as they are fast, non-destructive and easily applied. In this paper, the performance of quadratic discriminant functions and one form of artificial neural network are compared for the task of identifying Australian wheat varieties. This is a complex problem as the kernels are very similar in appearance, and factors other than variety significantly influence shape. It is shown both approaches have some similarity in performance, but discriminant functions provide a superior result and are more easily applied. There is, though, some opportunity for further refinement of the artificial neural network.

Paper Details

Date Published: 6 January 1995
PDF: 6 pages
Proc. SPIE 2345, Optics in Agriculture, Forestry, and Biological Processing, (6 January 1995); doi: 10.1117/12.198864
Show Author Affiliations
Douglas Graham Myers, Curtin Univ. (Australia)
Timo A. Vuori, Curtin Univ. (Australia)


Published in SPIE Proceedings Vol. 2345:
Optics in Agriculture, Forestry, and Biological Processing
George E. Meyer; James A. DeShazer, Editor(s)

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