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Proceedings Paper

Adaptive fuzzy approach to edge detection
Author(s): Petr Musilek; Madan M. Gupta; Gregory J. Schmidt
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Paper Abstract

Biological visual information processing can be divided into two processing levels: low level and high level.Low level visual processing includes several elementary operations allowing a reduction of the large amount of data present in a scene and from this recovering useful information at a higher level. An important operation is edge detection, which consists of image segmentation and consequent higher level processing for pattern classification and object recognition. Approaches to the edge detection problem vary from histogram based thresholding to biologically motivated gradient operators and discriminant functions. They provide edge detection of given images with various fidelities and at different computational expenses.

Paper Details

Date Published: 24 November 1999
PDF: 11 pages
Proc. SPIE 3832, Sensors and Controls for Intelligent Machining and Manufacturing Mechatronics, (24 November 1999); doi: 10.1117/12.371167
Show Author Affiliations
Petr Musilek, Univ. of Saskatchewan (Canada)
Madan M. Gupta, Univ. of Saskatchewan (Canada)
Gregory J. Schmidt, Univ. of Saskatchewan (Canada)


Published in SPIE Proceedings Vol. 3832:
Sensors and Controls for Intelligent Machining and Manufacturing Mechatronics
Patrick F. Muir; George K. Knopf; Patrick F. Muir; Peter E. Orban, Editor(s)

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