A Sign Language to Text Converter Using Leap Motion

Fazlur Rahman Khan (1), Huey Fang Ong (2), Nurhidayah Bahar (3)
(1) Faculty of Business & Information Science, UCSI University, Malaysia
(2) Faculty of Computing, University Malaysia of Computer Science & Engineering, Malaysia
(3) Faculty of Business & Information Science, UCSI University, Malaysia
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How to cite (IJASEIT) :
Khan, Fazlur Rahman, et al. “A Sign Language to Text Converter Using Leap Motion”. International Journal on Advanced Science, Engineering and Information Technology, vol. 6, no. 6, Dec. 2016, pp. 1089-95, doi:10.18517/ijaseit.6.6.1252.
This paper presents a prototype that can convert sign language into text. A Leap Motion controller was utilised as an interface for hand motion tracking without the need of wearing any external instruments. Three recognition techniques were employed to measure the performance of the prototype, namely the Geometric Template Matching, Artificial Neural Network and Cross Correlation. 26 alphabets from American Sign Language were chosen for training and testing the proposed prototype. The experimental results showed that Geometric Template Matching achieved the highest recognition accuracy compared to the other recognition techniques.

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