Gesture recognition system using 2D-invariant moment feature and Elman neural network

Authors:
M. P. Paulraj;C. R. Hema;Sazali Bin Yaacob;Mohd Shuhanaz Zanar Azalan;Rajkumar Palaniappan
Affiliations:
School of Mechatronic Engineering, University Malaysia Perlis, Perlis, 02600, Malaysia;Faculty of Engineering, Karpagam University, Coimbatore, 641 021, India;School of Mechatronic Engineering, University Malaysia Perlis, Perlis, 02600, Malaysia;School of Mechatronic Engineering, University Malaysia Perlis, Perlis, 02600, Malaysia;School of Mechatronic Engineering, University Malaysia Perlis, Perlis, 02600, Malaysia
Venue:
International Journal of Artificial Intelligence and Soft Computing
Year:
2013

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Abstract

This paper presents a simple sign language recognition system that has been developed using skin colour segmentation and Elman neural network. A simple segmentation process is carried out to separate the right and left hand. The 2D-invariant moments of the right and left hand segmented image are obtained as features. Using the 2D-invariant moment features, an Elman neural network model was developed. The system has been implemented and tested for its validity. Experimental results show that the system has a recognition rate of 90.63%.