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Proceedings Paper

X-ray agricultural product inspection: segmentation and classification
Author(s): David P. Casasent; Ashit Talukder; Ha-Woon Lee
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Paper Abstract

Processing of real-time x-ray images of randomly oriented and touching pistachio nuts for product inspection is considered. We describe the image processing used to isolate individual nuts (segmentation). This involves a new watershed transform algorithm. Segmentation results on approximately 3000 x-ray (film) and real time x-ray (linescan) nut images were excellent (greater than 99.9% correct). Initial classification results on film images are presented that indicate that the percentage of infested nuts can be reduced to 1.6% of the crop with only 2% of the good nuts rejected; this performance is much better than present manual methods and other automated classifiers have achieved.

Paper Details

Date Published: 18 September 1997
PDF: 10 pages
Proc. SPIE 3205, Machine Vision Applications, Architectures, and Systems Integration VI, (18 September 1997); doi: 10.1117/12.285589
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
Ashit Talukder, Carnegie Mellon Univ. (United States)
Ha-Woon Lee, Dongyang Univ. (South Korea)

Published in SPIE Proceedings Vol. 3205:
Machine Vision Applications, Architectures, and Systems Integration VI
Susan Snell Solomon; Bruce G. Batchelor; John W. V. Miller, Editor(s)

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