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A Digital Pen Based On Accelerometer for Handwritten Digit

Journal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.3, No. 8)

Publication Date:

Authors : ; ;

Page : 167-174

Keywords : Accelerometer; gesture; handwritten recognition; probabilistic neural network(PNN); linear discriminant analysis (LDA); RF wireless module; Microcontroller;

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Abstract

In this paper we proposed an Accelerometer based on Micro Electro Mechanical Systems. The (MEMS) which is used in Digital pan for handwritten Digit and Gesture recognition. The (MEMS) is composed of a accelerometer, microcontroller and wireless module RF. user can hold this pen and write digit in air at normal speed. During drawing or writing movements the inertial sensor signal generated for the movements are transmitted to a computer via the wireless module. After measurement of this acceleration signal we can recognize it by using trajectory recognition algorithm. In this trajectory recognition algorithm we are using the acceleration acquisition, signal preprocessing, feature generation and Probablistic Neural Network (PNN). The algorithm is capable of translating time-series acceleration signal into important feature vector. The trajectory recognition algorithm first extract the time-and frequency-domain features from the acceleration signals and, then, further apply two important feature i.e. Zero Crossing and Range Feature. Finally with the help of probabilistic neural network (PNN) we can recognize the digit. In this paper Our results have successfully validated the effectiveness of the trajectory recognition algorithm for handwritten digit using the proposed digital pen.

Last modified: 2014-09-03 15:07:55