Authors: Muhammad Faisal Zafar, Dzulkifli Mohamad, Razib M. Othman
Addresses: FSKSM, Universiti Teknologi Malaysia, 81300, Johor, Malaysia. ' FSKSM, Universiti Teknologi Malaysia, 81300, Johor, Malaysia. ' FSKSM, Universiti Teknologi Malaysia, 81300, Johor, Malaysia
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.
Keywords: pattern smoothing; handwriting recognition; direction vector encoding; feature extraction; isolated character recognition.
International Journal of Artificial Intelligence and Soft Computing, 2010 Vol.2 No.3, pp.186 - 198
Published online: 17 Feb 2011 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article