Effects of hyperellipsoidal decision surfaces on image segmentation in artificial color

Jian Fu; H. John Caulfield; Dongsheng Wu; Trent Montgomery

doi:10.1117/1.3377146

1 April 2010 Effects of hyperellipsoidal decision surfaces on image segmentation in artificial color

Jian Fu, H. John Caulfield, Dongsheng Wu, Trent Montgomery

Author Affiliations +

Journal of Electronic Imaging, Vol. 19, Issue 2, 023003 (April 2010). https://doi.org/10.1117/1.3377146

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.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Jian Fu, H. John Caulfield, Dongsheng Wu, and Trent Montgomery "Effects of hyperellipsoidal decision surfaces on image segmentation in artificial color," Journal of Electronic Imaging 19(2), 023003 (1 April 2010). https://doi.org/10.1117/1.3377146

Published: 1 April 2010

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