Paper
1 June 1992 Local operator for computing curvature
Ernest M. Stokely, Elizabeth Mazorra
Author Affiliations +
Abstract
Several approaches to medical image understanding require the measurement of curvature along the object boundary. Conventional methods for determining the curvature of an edge involve object segmentation and boundary tracking techniques. In this report, a local operator is described which computes curvature directly from either a gray scale or binary image without explicit detection of the edge. The operator defines two concentric circular boundaries which are used to map underlying pixel intensities into two 1-D functions. These functions are fit with a square wave which is optimum in the least-squares sense, providing four candidate points on an iso-intensity contour. By fitting a circle to this boundary, the curvature of the iso- intensity contour can be found as (kappa) equals 1/radius. A number of design questions are addressed, including the question of the correct relative size of the two concentric circles, and the method and threshold for rejecting uncertain determinations of the isocontour points due to noise. The operator is tested using simulated images, planar radiographs, and MR proton density images. Use of the operator in determining isocontours which have a specified curvature is demonstrated.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ernest M. Stokely and Elizabeth Mazorra "Local operator for computing curvature", Proc. SPIE 1652, Medical Imaging VI: Image Processing, (1 June 1992); https://doi.org/10.1117/12.59431
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Cited by 1 scholarly publication.
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KEYWORDS
Medical imaging

Image processing

Binary data

Magnetic resonance imaging

3D image processing

Image segmentation

Sensors

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