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Proceedings Paper

AGUILA: an automatic tube detection system
Author(s): Omid Mohtadi; Felix Safar; Jorge L. C. Sanz
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Paper Abstract

This paper discusses a system which uses machine vision algorithms for the detection of tubes in an extremely `noisy' industrial environment. The heart of the algorithm consists of sampling of the image in predefined sparse bands perpendicular to the likely orientation of the tubes followed by the application of a normalized correlation as a detection filter over these bands. After assigning a reliability factor to each local maxima of the correlation function, these points are then mapped to the Hough space to determine the equations of the midlines of the tubes. Given these equations, the number of tubes and any positional anomalies are reported.

Paper Details

Date Published: 1 March 1992
PDF: 12 pages
Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); doi: 10.1117/12.58596
Show Author Affiliations
Omid Mohtadi, IBM Argentina S.A. and Escuela Superior Latino Americana de Informatica (Argentina)
Felix Safar, IBM Argentina S.A. and Univ. Nacional de la Plata (Argentina)
Jorge L. C. Sanz, IBM/Almaden Research Ctr. (United States)
IBM Argentina S.A. (Argentina)


Published in SPIE Proceedings Vol. 1708:
Applications of Artificial Intelligence X: Machine Vision and Robotics
Kevin W. Bowyer, Editor(s)

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