Scheduled System Maintenance:
On Wednesday, July 29th, IEEE Xplore will undergo scheduled maintenance from 7:00-9:00 AM ET (11:00-13:00 UTC). During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Fuzzy Models for Low-Level Computer Vision: A Comprehensive Approach

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Russo, F. ; Trieste Univ., Trieste

It is well-known that fuzzy sets were conceived by Zadeh in 1965 as a mathematical tool able to model the concept of partial membership. After a period of theoretical investigation, in the mid- 1980s fuzzy rule-based methods became a problem solving technology and the engineering applications grew fast especially in the area of control systems. Low-level computer vision was a field where fuzzy modelling emerged as a very powerful resource too. The aim of this presentation is not to provide a thorough description of many different approaches that are currently available in the scientific literature. It aims rather at investigating how nowadays key operations such as noise removal, image sharpening and edge detection can be performed by adopting a comprehensive approach and simple fuzzy models.

Published in:

Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on

Date of Conference:

3-5 Oct. 2007