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Proceedings Paper

Edge Detection Using Maximum Likelihood Estimate Of Change Point: The One-Dimensional Case
Author(s): C. C. Li; M. Mazumdar; R. J. Chao
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Paper Abstract

This paper presents a method of edge detection incorporating maximum likelihood estimates of intensity change points in the noisy digital data. The method is developed in the context of the line scan where a sliding window of a reasonable size is used, and is applicable to edge detection in 2-D images by scanning both horizontally and vertically. With the proper choice of detector parameters, i.e., contrast threshold across an edge and count threshold of each estimate, the method can provide an accurate determination of edge locations for dimensional measurement in automated inspection.

Paper Details

Date Published: 18 May 1987
PDF: 6 pages
Proc. SPIE 0730, Automated Inspection and Measurement, (18 May 1987); doi: 10.1117/12.937865
Show Author Affiliations
C. C. Li, University of Pittsburgh (United States)
M. Mazumdar, University of Pittsburgh (United States)
R. J. Chao, University of Pittsburgh (United States)

Published in SPIE Proceedings Vol. 0730:
Automated Inspection and Measurement
Michael J. W. Chen; Robert H. Thibadeau, Editor(s)

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