By Topic

Robust line segment extraction using genetic algorithms

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 $31
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)
Mirmehdi, M. ; Surrey Univ., Guildford, UK ; Palmer, P.L. ; Kittler, J.

Success in scene interpretation in high level computer vision depends heavily on the quality of features derived from the low level stages of processing. We describe an optimisation process for robust low level feature extraction based on genetic optimisation. The fitness function is a performance measure which reflects the quality of an extracted set of features. We present some results and compare them with a hill-climbing optimisation approach

Published in:

Image Processing and Its Applications, 1997., Sixth International Conference on  (Volume:1 )

Date of Conference:

14-17 Jul 1997