By Topic

An evaluation of mesh model algorithms for direct feature detection on compressed image representations

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 $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)
Scotney, B.W. ; Dept. of Informatics, Ulster Univ., Coleraine, UK ; Coleman, S.A. ; Herron, M.G.

Recent developments in mesh modelling of images have provided algorithms that can achieve accurate and efficient image representations without the high computational cost associated with earlier optimisation-based methods. Hence nonuniform sampling of images combined with the use of irregular content-based meshing has provided a successful basis for recent developments in image compression techniques. The evaluation of these techniques has focussed on the accuracy and efficiency with which the mesh model can represent the image. For real-time applications, the usefulness of a mesh model may be assessed by its ability to yield compressed image representations that can be processed directly to provide output that is sufficiently accurate. Hence we present an evaluation of mesh model algorithms that is based on feature detection on the associated compressed image representations. Such an approach is built on the recent development of systematic design procedures for scalable and adaptive image processing operators that can be applied directly to non-uniformly sampled images. We demonstrate the approach using image derivative operators on compressed images.

Published in:

Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on  (Volume:1 )

Date of Conference:

14-17 Sept. 2003