NDLI: Malayalam online handwriting recognition system: A simplified fuzzy ARTMAP approach

Content Provider	IEEE Xplore Digital Library
Author	Indhu, T.R. Bhadran, V.K.
Copyright Year	2012
Description	Author affiliation: Centre for Development of Advanced Computing, Thiruvananthapuram, Kerala, India (Indhu, T.R.; Bhadran, V.K.)
Abstract	On-line handwriting recognition is the automatic conversion of handwritten text into letter codes as it is written on a special digitizer or PDA which is usable within computer and text-processing applications. Some of the commonly used techniques for online handwritten characters include Hidden Markov Model (HMM), elastic matching, structural analysis, Time delay neural networks, and combination of multiple classifiers. This paper describes Malayalam online handwriting recognition system using SFAM artificial neural network technique. The structural and directional information is extracted/collected from each character/stroke. The extracted features, which form the feature vector, are passed as input to a Simplified Fuzzy ARTMAP (SFAM) artificial neural network (ANN) classifier. The SFAM classifier compares the input data with the trained data and finds the nearest prototype from the database that ‘resonates’ with the input pattern. The labels or recognized characters are assigned their corresponding Unicode code points and displayed using appropriate fonts. Using this technique we have obtained an average accuracy of 98.26%.
Starting Page	613
Ending Page	618
File Size	823540
Page Count	6
File Format	PDF
ISBN	9781467322706
e-ISBN	9781467322720
DOI	10.1109/INDCON.2012.6420691
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-07
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Handwriting recognition Accuracy Malayalam Hidden Markov models Pre-processing Feature Extraction Feature extraction SFAM Vectors Online Handwriting Recognition Character recognition
Content Type	Text
Resource Type	Article

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