Performance analysis of a proposed smoothing algorithm for isolated handwritten characters
by Muhammad Faisal Zafar, Dzulkifli Mohamad, Razib M. Othman
International Journal of Artificial Intelligence and Soft Computing (IJAISC), Vol. 2, No. 3, 2010

Abstract: This paper describes an online isolated character recognition system using advanced techniques of pattern smoothing and Direction Feature (DF) extraction. The composition of direction elements and their smoothing are directly performed on online trajectory, and therefore, are computationally efficient. We compare recognition performance when DFs are formulated using Smoothed Direction Vectors (SDV) and Unsmoothed Direction Vectors (UDV). In experiments, direction features from original pattern yielded inferior performance, whereas primitive sub-character direction features using smoothed direction-encoded vectors made significant difference. Recognition rates were improved by about 7% and 5% using SDV when compared with UDV and smoothed with Moving Average (MA) technique, respectively.

Online publication date: Thu, 17-Feb-2011

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Artificial Intelligence and Soft Computing (IJAISC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com