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Proceedings Paper

A Local Curvature Operator
Author(s): Farhad A. Kamangar; Ernest M. Stokely
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Paper Abstract

A 2-D local operator is described for computing the local curvature of intensity isocontours in a digital image. The operator directly estimates the average local curvature of the isointensity contours, and does not require the explicit detection of edges. In a manner similar to the Hueckel operator, a series of 2D basis functions defined over a circular local neighborhood extract a set of coefficients from the image at each point of investigation. These coefficients describe an approximation to a circular arc assumed to pass through the neighborhood center, and the curvature is taken as the inverse of the estimated arc radius. The optimal set of basis functions for approximating this particular target pattern is shown to be the Fourier series. Discretization of the continuous basis functions can create anisotropy problems for the local operator; however, these problems can be overcome either by using a set of correction functions, or by choosing a discrete function which closely approximates the circular neighborhood. The method is validated using known geometric shapes and is shown to be accurate in estimating both curvature and the orientation of the isocontours. When applied to a test image the curvature operator provides regional curvature measurements compatible with visible edges in the image.

Paper Details

Date Published: 1 March 1990
PDF: 12 pages
Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); doi: 10.1117/12.969733
Show Author Affiliations
Farhad A. Kamangar, University of Texas at Arlington (United States)
Ernest M. Stokely, University of Texas at Arlington (United States)

Published in SPIE Proceedings Vol. 1192:
Intelligent Robots and Computer Vision VIII: Algorithms and Techniques
David P. Casasent, Editor(s)

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