영상처리 기반 숫자 수화표현 인식 알고리즘 = Numeric Sign Language Interpreting Algorithm Based on Hand Image Processing

다국어 초록 (Multilingual Abstract)

The existing auxiliary communicating aids for the hearing-impaired have an inconvenience of using additional expensive sensing devices. This paper presents a hand image detection based algorithm to interpret the sign language of the hearing-impaired. The proposed sign language recognition system exploits the hand image only captured by the camera without using any additional gloves with extra sensors. Based on the hand image processing, the system can perfectly classify several numeric sign language representations. This work proposes a simple lightweight classification algorithm to identify the hand image of the hearing-impaired to communicate with others even further in an environment of complex background. Experimental results show that the proposed system can interpret the numeric sign language quite well with an accuracy of 95.6% on average.

참고문헌 (Reference)

1 구성민, "청각장애인을 위한 오픈 소스 하드웨어 기반의 수화통역 장갑 & 상황 인지 보조 IoT 장치" 한국정보과학회 24 (24): 204-209, 2018

2 채수환, "노이즈에 강인한 HSV 색상 모델 기반손 윤곽 검출 시스템" 한국멀티미디어학회 18 (18): 1149-1156, 2015

3 "Wikipedia document (HSL and HSV)"

4 S. Glennen, "The Handbook of Augmentative and Alternative Communication" Singular Publishing Group, INC 1997

5 "Statistics Korea 1. (The Number of Registered Disabled Person – By City, Type, Gender) 2. (Characteristics of Hearing Disabled – Method to Communicate Who Mostly Use)"

6 Z. Zhengzhen, "Skin Color Detecting Unite YCgCb Color Space with YCgCr Color Space" 221-225, 2009

7 D.M. Capilla, "Sign Language Translator Using Microsoft Kinect XBOX 360™"

8 A. Kumar, "Sign Language Recognition" 2016

9 T. Lindeberg, "Scale Invariant Feature Transform" 7 (7): 10491-, 2012

10 "Python library"

11 M. Frenando, "Low Cost Approach for Real Time Sign Language Recognition" 18-20, 2013

12 A. Dhawan, "Implementation of Hand Detection based Techniques for Human Computer Interaction" 72 (72): 6-13, 2013

13 Y. Xu, "Identification of Hand Region Based on YCgCr Color Representation" 12 (12): 1031-1034, 2017

14 S. Kolkur, "Human Skin Detection Using RGB, HSV, and YCbCr Color Models" 2017

15 P. Molchanov, "Hand Gesture Recognition with 3D Convolutional Neural Networks" 1-7, 2015

16 R.N. Nagashree, "Hand Gesture Recognition Using Support Vector Machine" 4 (4): 42-46, 2015

17 "EnableTalk website"

18 W.Burger, "Digital Image Processing: An Algorithmic Introduction Using Java Second Edition" Springer 2016

19 S.S. Hazari, "Designing a Sign Language Translation System Using Kinect Motion Sensor Device" 16-18, 2017

20 J. Zhang, "Chinese Sign Language Recognition with Adaptive HMM" 1-6, 2016

21 C. Dong, "American Sign Language Alphabet Recognition Using Microsoft Kinect" 44-25, 2015

22 Joshua R. New, "A Method for Hand Gesture Recognition" 919-923, 2002