Simple glove-based Korean finger spelling recognition system

Authors:
Seungki Min;Sanghyeok Oh;Gyoryeong Kim;Taehyun Yoon;Chungyu Lim;Yunli Lee;Keechul Jung
Affiliations:
HCI Lab, Department of Digital Media, Soongsil University, Seoul, Korea;HCI Lab, Department of Digital Media, Soongsil University, Seoul, Korea;HCI Lab, Department of Digital Media, Soongsil University, Seoul, Korea;HCI Lab, Department of Digital Media, Soongsil University, Seoul, Korea;HCI Lab, Department of Digital Media, Soongsil University, Seoul, Korea;HCI Lab, Department of Digital Media, Soongsil University, Dongjak-Gu, Seoul, Korea;HCI Lab, Department of Digital Media, Soongsil University, Dongjak-Gu, Seoul, Korea
Venue:
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Year:
2007

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Abstract

In this paper, we present the development of a simple and low cost data glove system using tilt and flex sensors as a Korean Finger Spelling (KFS) recognition system. This data glove has the capability to measure the palm and finger gesture postures. The process of building a simple KFS recognition system and method for recognizing the KFS letters is also proposed in this paper. The k-means algorithm is used to classify the KFS letter's based on tilt sensor measurement. The flex sensor measurement on each finger is divided into three main bending positions and quantization index rule-based is used to recognize the KFS letters. For the convenience of using this glove, a simple and efficient calibration process of the finger gesture is provided, so that all the required parameters for recognition can be adapted automatically. The system gives an average of 80% correct recognition for the 24 letters in KFS. The glove-based KFS is possibility to ease and encourage the Korean community to learn KFS by providing hands-on and minds-on learning experiences with an affordable data glove.