By Topic

Well-distributed SIFT features

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
$33 $33
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

2 Author(s)
R. Song ; University of York, York YO10 5DD, United Kingdom ; J. Szymanski

A method to enhance the recognition of spatially distributed features, based on the scale invariant feature transform (SIFT), is reported. The key idea is to modify the way in which the selection of a set of contender interest points from each input image is carried out, using a non-maximal suppression approach in the different scale spaces.

Published in:

Electronics Letters  (Volume:45 ,  Issue: 6 )