The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 29-133
Full Name: IDRESS El-FeghI
Position: Assistant Professor
Age: ON
Sex: Male
Address: Sirt Libya P.O. Box 727
Country: LIBYA
Tel: +218913752962
Tel prefix:
Fax:
E-mail address: idrisel@gmail.com
Other E-mails:
Title of the Paper: Using Zernike Moments as Features for Handwritten Arabic Numeric word
Authors as they appear in the Paper: . El-Feghi1,Zakaria Suliman Zubi2, Ali .A.Elrowayati3 ,Faraj A. El-Mouadib4
Email addresses of all the authors: idrisel@gmail.com, zszubi@yahoo.com, arwyate@yahoo.com, elmouadib@yahoo.com
Number of paper pages: 10
Abstract: Abstract:- This paper presents the application of Multi Layer Perceptron (MLP) Artificial Neural Network to classification of handwritten Arabic words. Zernik Moments are used as a feature vector for each word. An efficient way to select the most suitable order of Zernik moments is also presented. The MLP is trained in a supervised fashion using the Back Propagation learning algorithm. Having being trained, the MLP is tested on different set of handwritten Arabic words that has never been seen by the MLP. Several experiments are performed to select the best MLP structure. Experimental results have shown that with the presented structure and the order of the Zernik Moments more than 87% of correct recognition was obtained.
Keywords: Keywords:- Zernik Moments, Multi Layer Perceptron, Artificial Neural Networks, Handwritten Arabic Recognition.
EXTENSION of the file: .doc
Special (Invited) Session: Handwritten Arabic Words Recognition using Multi Layer Perceptron and Zernik Moments
Organizer of the Session: 611-191
How Did you learn about congress:
IP ADDRESS: 193.179.46.52
