By Topic

Neural network based textural labeling of images in multimedia applications

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)
Karkanis, S.A. ; Dept. of Inf., Athens Univ., Greece ; Magoulas, G.D. ; Karras, D.A. ; Grigoriadou, M.

In this paper the use of multilayer perceptron type neural networks in the characterization of images by texture content is investigated. The paper is focused on the effects of textural feature extraction methods on the network architecture, training performance and generalization capability when applied to indexing of images in multimedia image databases. An in depth experimental study is conducted comparing several well known textural feature extraction techniques along with a novel discrete wavelet transform based methodology. It is demonstrated that the proposed technique leads to the design and selection of multilayer perceptron architectures with the best texture classification accuracy

Published in:

EUROMICRO Conference, 1999. Proceedings. 25th  (Volume:2 )

Date of Conference:

1999