Writing in the Air Using Kinect and Growing Neural Gas Network

Authors

  • Mohammad Reza Aminian Heidari Universiti Kebangsaan Malaysia, Bangi, Malaysia
  • Azrulhizam Shapi’i Universiti Kebangsaan Malaysia, Bangi, Malaysia
  • Riza Sulaiman Universiti Kebangsaan Malaysia, Bangi, Malaysia

DOI:

https://doi.org/10.11113/jt.v72.3949

Keywords:

Kinect, growing neural gas, multi-layer perceptron network

Abstract

This paper discusses an approach which helps us to recognize English language characters which are written in the air by hands. This method is done by using Kinect camera and growing neural gas network. The proposed character recognition method has three main steps: preprocessing, training and recognition. The system and the proposed method can be considered from two aspects: (a) runtime, and (b) accuracy. One of the main goals in this method is to provide noise tolerance which is necessary for these kinds of methods. IN addition, it has influence upon accuracy rate because the proposed method can remove more outliers. The results show that the proposed method provides good results with the accuracy rate of 95.54%, 97.86% and 99.08% for lower case letters, upper case letters and digits respectively.

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Published

2015-01-11

How to Cite

Writing in the Air Using Kinect and Growing Neural Gas Network. (2015). Jurnal Teknologi, 72(5). https://doi.org/10.11113/jt.v72.3949