Hand Gesture Recognition for Disaster Management Applications

被引:3
|
作者
Sumalatha, R. [1 ]
Rajasekhar, D. [1 ]
Rao, R. Vara Prasada [2 ]
机构
[1] G Pullaiah Coll Engn & Technol, Kurnool, India
[2] Rajiv Gandhi Mem Coll Engn & Technol, Kurnool, India
来源
ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2017 | 2018年 / 668卷
关键词
Disaster management; Hand gesture recognition; Mining; RGB to HSV; Text to speech; Euclidian distance;
D O I
10.1007/978-981-10-7868-2_45
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper discusses about hand gesture recognition for disaster management like mining. In mining places, so many workers are always in danger situation. If the mine falls down suddenly then working people would be under the coal. If anyone is alive, but not able be to communicate with the rescue team in this situation working people may be dead. For saving their lives the proposed system provides facility to the working people send the information through hand gesture to rescue office. The proposed system is designed to recognize hand gestures using simple color feature extraction algorithm. After extracting the color feature of the test and training images we calculated the Euclidian distance to recognize the hand gesture. Finally, the recognized gesture image corresponding text can be converted into speech.
引用
收藏
页码:465 / 471
页数:7
相关论文
共 50 条
  • [41] Hand Gesture Recognition using CVZONE
    Nguyen, Hao A.
    Tran, Thien T.
    Ho, Hien Q.
    Ngo, Toan D.
    Vu, Khanh N.
    Huynh, Viet L. T.
    PROCEEDINGS OF THE 2024 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION TECHNOLOGY, ICIIT 2024, 2024, : 108 - 113
  • [42] Hand gesture recognition, a stochastic approach
    Teruel, LE
    Kubushyna, O
    Yfantis, EA
    Stubberud, PA
    Hwang, CJ
    Bebis, G
    Boyle, R
    PROCEEDINGS OF THE ISCA 12TH INTERNATIONAL CONFERENCE INTELLIGENT AND ADAPTIVE SYSTEMS AND SOFTWARE ENGINEERING, 2003, : 140 - 143
  • [43] SHAPE: a dataset for hand gesture recognition
    Dang, Tuan Linh
    Nguyen, Huu Thang
    Dao, Duc Manh
    Nguyen, Hoang Vu
    Luong, Duc Long
    Nguyen, Ba Tuan
    Kim, Suntae
    Monet, Nicolas
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (24): : 21849 - 21862
  • [44] Study on Techniques of Hand Gesture Recognition
    Mi, Shoufang
    Li, Linghua
    INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS, PTS 1-4, 2013, 241-244 : 1664 - 1667
  • [45] Dynamic Hand Gesture Recognition Using the Skeleton of the Hand
    Bogdan Ionescu
    Didier Coquin
    Patrick Lambert
    Vasile Buzuloiu
    EURASIP Journal on Advances in Signal Processing, 2005
  • [46] Comparison of Hand Segmentation Methodologies for Hand Gesture Recognition
    Howe, Lim Wei
    Wong, Farrah
    Chekima, Ali
    INTERNATIONAL SYMPOSIUM OF INFORMATION TECHNOLOGY 2008, VOLS 1-4, PROCEEDINGS: COGNITIVE INFORMATICS: BRIDGING NATURAL AND ARTIFICIAL KNOWLEDGE, 2008, : 914 - 920
  • [47] Trajectory based hand gesture recognition
    Popa, Daniel
    Simion, Georgiana
    Gui, Vasile
    Otesteanu, Marius
    CIMMACS '07: PROCEEDINGS OF THE 6TH WSEAS INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE, MAN-MACHINE SYSTEMS AND CYBERNETICS, 2007, : 115 - +
  • [48] A Review on Hand Gesture Recognition System
    Sonkusare, Jayesh S.
    Chopade, Nilkanth. B.
    Sor, Ravindra
    Tade, Sunil L.
    1ST INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION ICCUBEA 2015, 2015, : 790 - 794
  • [49] Hand Gesture Recognition by Thinning Method
    Rokade, Rajeshree
    Doye, Dharmpal
    Kokare, Manesh
    ICDIP 2009: INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING, PROCEEDINGS, 2009, : 284 - 287
  • [50] Hand Gesture Recognition with Leap Motion
    Feng, Lin
    Du, Youchen
    Liu, Shenglan
    Xu, Li
    Wu, Jie
    Qiao, Hong
    PROCEEDINGS OF THE FUTURE TECHNOLOGIES CONFERENCE (FTC) 2018, VOL 1, 2019, 880 : 46 - 54