By Topic

Adaptive filtering of distorted displacement vector fields using artificial neural networks

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

4 Author(s)
Michaelis, B. ; Inst. for Measure. & Electron., Otto-von-Guericke Univ. of Magdeburg, Germany ; Schnelting, O. ; Seiffert, U. ; Mecke, R.

In this paper the utilization of artificial neural networks (ANN) for motion estimation is considered. By means of simple neural structures it is possible to improve the reliability and accuracy of block matching algorithms (BMA) by a postprocessing of the similarity criterion. An associative memory realizes an adaptive choice of these filtering structures depending on the image contents. The fundamental idea and some results will be described. The performance capability of the proposed method is shown for selected two-dimensional measuring situations which are not solvable with conventional BMA

Published in:

Pattern Recognition, 1996., Proceedings of the 13th International Conference on  (Volume:4 )

Date of Conference:

25-29 Aug 1996