Adaptive fuzzy approach to edge detection

Petr Musilek; Madan M. Gupta; Gregory J. Schmidt

doi:10.1117/12.371167

24 November 1999 Adaptive fuzzy approach to edge detection

Petr Musilek, Madan M. Gupta, Gregory J. Schmidt

Proceedings Volume 3832, Sensors and Controls for Intelligent Machining and Manufacturing Mechatronics; (1999) https://doi.org/10.1117/12.371167
Event: Photonics East '99, 1999, Boston, MA, United States

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.

Citation Download Citation

Petr Musilek, Madan M. Gupta, and Gregory J. Schmidt "Adaptive fuzzy approach to edge detection", Proc. SPIE 3832, Sensors and Controls for Intelligent Machining and Manufacturing Mechatronics, (24 November 1999); https://doi.org/10.1117/12.371167

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