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Proceedings Paper

Neural net classification of x-ray pistachio nut data
Author(s): David P. Casasent; Michael A. Sipe; Thomas F. Schatzki; Pamela M. Keagy; Lan Chau Le
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Paper Abstract

Classification results for agricultural products are presented using a new neural network. This neural network inherently produces higher-order decision surfaces. It achieves this with fewer hidden layer neurons than other classifiers require. This gives better generalization. It uses new techniques to select the number of hidden layer neurons and adaptive algorithms that avoid other such ad hoc parameter selection problems; it allows selection of the best classifier parameters without the need to analyze the test set results. The agriculture case study considered is the inspection and classification of pistachio nuts using x- ray imagery. Present inspection techniques cannot provide good rejection of worm damaged nuts without rejecting too many good nuts. X-ray imagery has the potential to provide 100% inspection of such agricultural products in real time. Only preliminary results are presented, but these indicate the potential to reduce major defects to 2% of the crop with 1% of good nuts rejected. Future image processing techniques that should provide better features to improve performance and allow inspection of a larger variety of nuts are noted. These techniques and variations of them have uses in a number of other agricultural product inspection problems.

Paper Details

Date Published: 18 December 1996
PDF: 11 pages
Proc. SPIE 2907, Optics in Agriculture, Forestry, and Biological Processing II, (18 December 1996); doi: 10.1117/12.262861
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
Michael A. Sipe, Carnegie Mellon Univ. (United States)
Thomas F. Schatzki, USDA Agricultural Research Service (United States)
Pamela M. Keagy, USDA Agricultural Research Service (United States)
Lan Chau Le, USDA Agricultural Research Service (United States)

Published in SPIE Proceedings Vol. 2907:
Optics in Agriculture, Forestry, and Biological Processing II
George E. Meyer; James A. DeShazer, Editor(s)

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