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Proceedings Paper

Line model for multisignature Gibbs classification
Author(s): Ian R. Greenshields; Junchul Chun
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Paper Abstract

The performance of the Gibbs Classifier over a statistically heterogeneous image can be improved if the locally stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at the local neighborhood level. This usually involves the construction of a line process for the image. In this paper we describe a method for constructing a line process for multisignature images based on the differential (total derivative) of the image which, when expressed statistically, can provide an a priori estimate of the line field.

Paper Details

Date Published: 6 January 1994
PDF: 9 pages
Proc. SPIE 2348, Imaging and Illumination for Metrology and Inspection, (6 January 1994); doi: 10.1117/12.198857
Show Author Affiliations
Ian R. Greenshields, Univ. of Connecticut (United States)
Junchul Chun, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 2348:
Imaging and Illumination for Metrology and Inspection
Donald J. Svetkoff, Editor(s)

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