By Topic

A new approach to object classification in binary images

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

2 Author(s)
Randolph, T.R. ; Center for Signal & Image Process., Georgia Inst. of Technol., Atlanta, GA, USA ; Smith, M.J.T.

In this paper, we address the problem of classifying binary objects using a cascade of a binary directional filter bank (DFB) and a higher-order neural network (HONN). The binary DFB receives as input a binary image and returns as output a binary subband representation. Because processing is performed on a finite field, the DFB is able to operate efficiently. Furthermore, the DFB provides a representation that delineates the directional components in the image, which enables the HONN to exploit the underlying shape of the object effectively. The paper provides a description of the new binary DFB and its use with the HONN, all in the context of object classification

Published in:

Electronics, Circuits and Systems, 2000. ICECS 2000. The 7th IEEE International Conference on  (Volume:1 )

Date of Conference:

2000