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Proceedings Paper

Robust object representation through object-relevant use of scale
Author(s): Bryan S. Morse; Stephen M. Pizer; Daniel S. Fritsch
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Paper Abstract

In previously published papers we have presented an object representation known as a core that represents an object at measurement scales (tolerances) relative to the local size of the object. Such object-relevant scale allows one to be more sensitive to such detail (and, of course, the effects of noise, blurring, and other image degradation) for smaller objects while being less sensitive to such detail (and image degradation) for larger objects. This produces a more robust mechanism that is able to trade off between sensitivity to noise and loss of detail by considering the properties of the object involved. This paper, after briefly reviewing the definition and computation of cores, studies this relationship between noise and object size and shows that the algorithms for computing cores do indeed produce more stable results for larger objects by automatically selecting correspondingly larger, less noise-sensitive scales.

Paper Details

Date Published: 11 May 1994
PDF: 12 pages
Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); doi: 10.1117/12.175046
Show Author Affiliations
Bryan S. Morse, Univ. of North Carolina/Chapel Hill (United States)
Stephen M. Pizer, Univ. of North Carolina/Chapel Hill (United States)
Daniel S. Fritsch, Univ. of North Carolina/Chapel Hill (United States)


Published in SPIE Proceedings Vol. 2167:
Medical Imaging 1994: Image Processing
Murray H. Loew, Editor(s)

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