Japanese Hand Sign Recognition System

Authors:
Hirotada Fujimura;Yuuichi Sakai;Hiroomi Hikawa
Affiliations:
Oita University, Oita, Japan 870-1192;Oita University, Oita, Japan 870-1192;Oita University, Oita, Japan 870-1192
Venue:
Neural Information Processing
Year:
2007

Citing 5
Cited 0

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Abstract

This paper discusses a Japanese hand sign recognition system with a simple classifier network. In the system, input hand images are preprocessed through horizontal/vertical projection followed by discrete Fourier transforms (DFTs) that calculate the magnitude spectrum. The magnitude spectrum is used as the feature vector. Use of the magnitude spectrum makes the system very robust against the position changes of the hand image. The final classification is carried out by the classifier network, which uses simple neurons. Each neuron evaluates the possibility of the input vector belonging to assigned cluster. From the evaluation results, the hand sign is identified. The feasibility of the system is verified by simulations. The simulation results show that the average recognition rate of the system is 93% even though the hand positions are changed randomly.