By Topic

Combining a fuzzy rule-based classifier and illumination Invariance for improved building detection

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

3 Author(s)
Zeljkovic, V. ; Fac. of Tech. Sci., Novi Sad, Serbia ; Dorado, A. ; Izquierdo, E.

The problem of edge-based classification of natural video sequences containing buildings and captured under changing lighting conditions is addressed in this letter. The introduced approach is derived from two empiric observations: In static regions the likelihood of finding features that match the patterns of "buildings" is high because buildings are rigid static objects; and misclassification can be reduced by filtering out image regions changing or deforming in time. These regions may contain objects semantically different to buildings but with a highly similar edge distribution, e.g., high frequency of vertical and horizontal edges. Using these observations a strategy is devised in which a fuzzy rule-based classification technique is combined with a method for changing region detection in outdoor scenes. The proposed approach has been implemented and tested with sequences showing changes in the lighting conditions. Selected results from the experimental evaluation are reported.

Published in:

Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:14 ,  Issue: 11 )