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http://dx.doi.org/10.9708/jksci.2019.24.02.193

Sign Language Image Recognition System Using Artificial Neural Network  

Kim, Hyung-Hoon (Dept. of Cosmetic Science, Kwangju Womens University)
Cho, Jeong-Ran (Dept. of Health Administration, Kwangju Womens University)
Publication Information
Journal of the Korea Society of Computer and Information / v.24, no.2, 2019 , pp. 193-200 More about this Journal
Abstract
Hearing impaired people are living in a voice culture area, but due to the difficulty of communicating with normal people using sign language, many people experience discomfort in daily life and social life and various disadvantages unlike their desires. Therefore, in this paper, we study a sign language translation system for communication between a normal person and a hearing impaired person using sign language and implement a prototype system for this. Previous studies on sign language translation systems for communication between normal people and hearing impaired people using sign language are classified into two types using video image system and shape input device. However, existing sign language translation systems have some problems that they do not recognize various sign language expressions of sign language users and require special devices. In this paper, we use machine learning method of artificial neural network to recognize various sign language expressions of sign language users. By using generalized smart phone and various video equipment for sign language image recognition, we intend to improve the usability of sign language translation system.
Keywords
Sign Language Translation; Artificial Neural Network; Machine Learning; Image Recognition; Hearing Impaired Person;
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Times Cited By KSCI : 1  (Citation Analysis)
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