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Journal of Electronic Imaging

Effects of hyperellipsoidal decision surfaces on image segmentation in artificial color
Author(s): Jian Fu; H. John Caulfield; Dongsheng Wu; Trent Montgomery
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Paper Abstract

Artificial color uses the projection of the spectrum into two or more broad, overlapping spectral bands to discriminate, pixel by pixel, among user-defined classes of objects. As initially practiced, it used a sequence of hyperspherical regions of the decision space to define class membership. Of course, a hypersphere is just a degenerate hyperellipsoid; thus, exploring the effect of loosening that degeneracy seemed appropriate. Initially, we use two-foci hyperellipsoids with a hyperellipsoidal distance metric to classify pixels with dramatic improvement in performance. We explore the work even further by allowing many foci and noting the effects of increased complexity of the decision surfaces. In the example case, three foci gave superior performance to one or two foci, but four added little improvement.

Paper Details

Date Published: 1 April 2010
PDF: 10 pages
J. Electron. Imag. 19(2) 023003 doi: 10.1117/1.3377146
Published in: Journal of Electronic Imaging Volume 19, Issue 2
Show Author Affiliations
Jian Fu, Alabama A&M Univ. (United States)
H. John Caulfield, Alabama A&M Univ. (United States)
Dongsheng Wu, The Univ. of Alabama in Huntsville (United States)
Trent Montgomery, Alabama A&M Univ. (United States)

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