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Proceedings Paper

New data clustering for RBF classifier of agriculture products from x-ray images
Author(s): David P. Casasent; Xuewen Chen
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Paper Abstract

Classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a subsystem for automated non-invasive detection of defective product items on a conveyor belt. We discuss the use of clustering and how it is vital to achieve useful classification. New clustering methods using class identify and new cluster classes are advanced and shown to be of use for this application. Radial basis function neural net classifiers are emphasized. We expect our results to be of use for other classifiers and applications.

Paper Details

Date Published: 26 August 1999
PDF: 10 pages
Proc. SPIE 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision, (26 August 1999); doi: 10.1117/12.360302
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
Xuewen Chen, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 3837:
Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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