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Proceedings Paper

Expanded image database of pistachio x-ray images and classification by conventional methods
Author(s): Pamela M. Keagy; Thomas F. Schatzki; Lan Chau Le; David P. Casasent; David Weber
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Paper Abstract

In order to develop sorting methods for insect damaged pistachio nuts, a large data set of pistachio x-ray images (6,759 nuts) was created. Both film and linescan sensor images were acquired, nuts dissected and internal conditions coded using the U.S. Grade standards and definitions for pistachios. A subset of 1199 good and 686 insect damaged nuts was used to calculate and test discriminant functions. Statistical parameters of image histograms were evaluated for inclusion by forward stepwise discrimination. Using three variables in the discriminant function, 89% of test set nuts were correctly identified. Comparable data for 6 human subjects ranged from 67 to 92%. If the loss of good nuts is held to 1% by requiring a high probability to discard a nut as insect damaged, approximately half of the insect damage present in clean pistachio nuts may be detected and removed by x-ray inspection.

Paper Details

Date Published: 18 December 1996
PDF: 9 pages
Proc. SPIE 2907, Optics in Agriculture, Forestry, and Biological Processing II, (18 December 1996); doi: 10.1117/12.262859
Show Author Affiliations
Pamela M. Keagy, USDA Agricultural Research Service (United States)
Thomas F. Schatzki, USDA Agricultural Research Service (United States)
Lan Chau Le, USDA Agricultural Research Service (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)
David Weber, Carnegie Mellon Univ. (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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