Online Pen Stroke Identification using Generalization Techniques of Artificial Neural Network

Ramya, S N and Kumara, Shama (2013) Online Pen Stroke Identification using Generalization Techniques of Artificial Neural Network. In: Proceedings of International Conference on Multimedia Processing, Communication and Information Technology, 19th to 21st December 2013, Shimoga, Karnataka, India.

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Abstract

Owing to the increase of pen computing applicationsand new pen input devices such as pen Tablet, pen basedmobile etc., Online Handwriting Recognition is gaining renewedinterests. In Online systems, handwriting data is captured duringthe writing process, which makes available the information onthe ordering of the strokes that are represented by a sequence ofcoordinate points between pen-down and pen-up. In this researchwe have collected online strokes using digitizer and saved in XMLformat. The data is preprocessed and the angular informationfor successive neighbors is extracted. Extracted features given asinput to the Feed Forward Neural Network model with supervisedtraining for the identification of stroke. The performance of thesystem is evaluated for generalization capability of the NeuralNetwork on pen strokes

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Online Strokes, Online Handwriting Recognition,Artificial Neural Network.
Subjects: Engineering > MIT Manipal > Electronics and Communication
Depositing User: MIT Library
Date Deposited: 25 Feb 2016 14:16
Last Modified: 01 Mar 2016 14:37
URI: http://eprints.manipal.edu/id/eprint/145391

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