Digital Pen for Handwritten Digit and Gesture Recognition Using Trajectory Recognition Algorithm Based On Triaxial Accelerometer- A Review

In this review paper we are going to discuss a systematic trajectory recognition algorithm framework that can construct effective classifiers for hand writing & gesture identification. Review of Digital Pen for Handwritten Digit and Gesture Recognition using Trajectory Recognition Algorithm based on Accelerometer is discuss for the identification of 2-D handwriting digits and 3-D hand gestures. for this implementation we are going to use triaxial accelerometer, a microcontroller, and an RF wireless transmission module for sensing and collecting accelerations of handwriting and gesture trajectories. The proposed trajectory recognition algorithm composes of the procedures of acceleration acquisition, signal reprocessing, feature generation, feature selection, and feature extraction. The algorithm is capable of translating time-series acceleration signals into important feature vectors. Users can use the pen to write digits or make hand gestures, and the accelerations of hand motions measured by the accelerometer are wirelessly transmitted to a computer for online trajectory recognition. Basically this algorithm is divided in two parts. First part is discussion about the implemented for the Handwritten Digit Recognition while in second part is discussion about the implemented for the Gesture Recognition. Keywords-Human–Computer Interaction (HCI), Micro Inertial Measurement Unit (μIMU), Optical Tracking System (OTS), Hidden Markov Model (HMM),linear discriminate analysis (LDA), probabilistic neural network (PNN), Ubiquitous Digital Writing Instrument (UDWI).