Comparison of Elastic Matching Algorithms for Online Tamil Handwritten Character Recognition
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
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Online handwriting recognition systems have been developed for various character sets. Despite that, very less attempt has been made to build an online handwriting recognition system for Indian languages. We present an online handwritten isolated character recognition system for an Indian language, Hindi, for mobile devices. Developing an online handwriting recognition system for Hindi character set to mobile devices would play an important role in making these devices available and usable for the Indian society. In this paper, we present a model for writer-independent online handwriting character recognition for the 49 basic Hindi characters. The proposed system is implemented on mobile device using two different approaches namely Principal Component Analysis (PCA) and Dynamic Time Wrapping (DTW). To find the suitability of these two approaches for handheld devices several experiments were conducted and detailed analysis has been made on the obtained results. The results obtained for PCA approach is quite promising than DTW. On an average, recognition accuracy up to 86% is achieved for the PCA approach and up to 66% is achieved for DTW approach, also the time taken for recognition of unknown character is around 0.8sec for PCA approach, and around 51sec for DTW approach, thus the PCA approach is suitable for real-time applications.