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Proceedings Paper

Stochastic recognition of closed object boundaries in images
Author(s): Jeffrey D. Helterbrand; Noel A. C. Cressie
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Paper Abstract

Engineering-based edge detection techniques generally use local intensity information to identify whether a pixel location is part of a boundary. Boundaries are presumed present where sharp transitions in the observed intensities occur. Unfortunately, these approaches are sensitive to error and hidden partial boundaries, which hinder the determination of closed object boundaries. In this research, a method to obtain statistically optimal closed object boundaries is presented.

Paper Details

Date Published: 23 June 1993
PDF: 12 pages
Proc. SPIE 2030, Image Algebra and Morphological Image Processing IV, (23 June 1993); doi: 10.1117/12.146664
Show Author Affiliations
Jeffrey D. Helterbrand, Iowa State Univ. (United States)
Noel A. C. Cressie, Iowa State Univ. (United States)


Published in SPIE Proceedings Vol. 2030:
Image Algebra and Morphological Image Processing IV
Edward R. Dougherty; Paul D. Gader; Jean C. Serra, Editor(s)

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