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Proceedings Paper

Quantitative core-based shape comparison
Author(s): Kevin O. Lepard; Richard A. Robb
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Paper Abstract

Comparison of shapes is at best a difficult problem. Although many methods of measuring shapes are available, such as circularity, Fourier descriptors, and invariant moments, these methods generally suffer from one or more of the following drawbacks, (1) requiring previous segmentation of the shape, (2) inability to relate the metric intuitively to the shape, and (3) inability to describe local features of object shape. We describe two new metrics based on cores: the average chamfer distance and the average fractional difference. These metrics do not require prior segmentation of objects, can be used to describe local features of object shape, and are intuitively related to degree of shape similarity or dissimilarity. Furthermore, we demonstrate that these metrics are well-behaved, producing output that varies in a predictable fashion, increasing in value as shapes become increasingly different and decreasing in value as shapes become increasing similar.

Paper Details

Date Published: 25 April 1997
PDF: 12 pages
Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274176
Show Author Affiliations
Kevin O. Lepard, Mayo Clinic and Foundation (United States)
Richard A. Robb, Mayo Clinic and Foundation (United States)


Published in SPIE Proceedings Vol. 3034:
Medical Imaging 1997: Image Processing
Kenneth M. Hanson, Editor(s)

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