Performance analysis of a proposed smoothing algorithm for isolated handwritten characters

Authors:
Muhammad Faisal Zafar;Dzulkifli Mohamad;Razib M. Othman
Affiliations:
FSKSM, Universiti Teknologi Malaysia, 81300, Johor, Malaysia.;FSKSM, Universiti Teknologi Malaysia, 81300, Johor, Malaysia.;FSKSM, Universiti Teknologi Malaysia, 81300, Johor, Malaysia
Venue:
International Journal of Artificial Intelligence and Soft Computing
Year:
2010

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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.