By Topic

Fourier fuzzy neural network for clustering of visual objects based on their gross shape and its application to handwritten character recognition

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

5 Author(s)
Patil, P.M. ; Dept. of Electron. & Comput. Sci. & Eng., SGGS Coll. of Eng. & Technol., Vishnupuri, India ; Deshmukh, M. ; Bonde, P.V. ; Dhabe, P.S.
more authors

In this paper, an unsupervised feedforward Fourier fuzzy neural network (FFNN) is proposed which is suitable for clustering of object images based on their gross shapes. This 3-layer feedforward neural network is described along with its training. Its performance is tested for synthetic image database containing objects of various shapes and with realistic image database of handwritten Devanagari digits. FFNN is found as superior to the fuzzy min-max neural network (FMN) clustering, and it takes less recall time per pattern than FMN.

Published in:

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on  (Volume:3 )

Date of Conference:

25-29 July 2004