Handwritten Character Recognition in the Air by Using Leap Motion Controller

被引:4
|
作者
Tsuchida, Kazuki [1 ]
Miyao, Hidetoshi [1 ]
Maruyama, Minoru [1 ]
机构
[1] Shinshu Univ, Comp Sci & Engn, Nagano, Japan
关键词
Character recognition; Leap motion; DP matching;
D O I
10.1007/978-3-319-21380-4_91
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In order to develop a system which can precisely and quickly recognize handwritten characters in the air by using a Leap Motion Controller, we propose the following method: (1) A user has to register handwritten characters as template patterns before use. Each pattern is represented by a sequence of motion vectors calculated by using adjacent sampling data. (2) In the recognition phase, an input pattern is represented in the same method as above. The input pattern is compared with each of the registered template patterns by using DP matching and we can obtain a distance (degree of similarity) between them. Our system outputs the character class corresponding to the pattern with a minimum distance as a recognition result. In our experiments for recognition of 46 Japanese hiragana characters and 26 alphabets, a high average recognition rate of 86.7 % and a short average processing time of 196 ms were obtained.
引用
收藏
页码:534 / 538
页数:5
相关论文
共 50 条
  • [31] Hindi Handwritten Character Recognition using Multiple Classifiers
    Yadav, Madhuri
    Purwar, Ravindra
    PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE AND ENGINEERING (CONFLUENCE 2017), 2017, : 149 - 154
  • [32] Ergonomic Quadcopter Control Using The Leap Motion Controller
    Gubcsi, Gergely
    Zsedrovits, Tamas
    2018 IEEE INTERNATIONAL CONFERENCE ON SENSING, COMMUNICATION, AND NETWORKING (SECON WORKSHOPS), 2018, : 49 - 53
  • [33] Handwritten character recognition using nonsymmetrical perceptual zoning
    Freitas, Cinthia O. A.
    Oliveira, Luiz S.
    Bortolozzi, Flavio
    Aires, Simone B. K.
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2007, 21 (01) : 135 - 155
  • [34] Handwritten Character Recognition Using Deep-Learning
    Vaidya, Rohan
    Trivedi, Darshan
    Satra, Sagar
    Pimpale, Mrunalini
    PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT), 2018, : 772 - 775
  • [35] Handwritten Character Recognition using Hierarchical Graph Matching
    Al Mubarok, Abdulloh
    Nugroho, Hertog
    2016 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND INFORMATION SYSTEMS (ICACSIS), 2016, : 454 - 459
  • [36] Analysis on Handwritten Bangla Character Recognition Using ANN
    Rahaman, Arifur
    Hasan, Md Mehedi
    Shuvo, Md Faisal
    Ovi, Md Abu Saleh
    Rahman, Md Mostafizur
    2014 INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION (ICIEV), 2014,
  • [37] Unconstrained handwritten character recognition using metaclasses of characters
    Koerich, AL
    Kalva, PR
    2005 International Conference on Image Processing (ICIP), Vols 1-5, 2005, : 2045 - 2048
  • [38] Using eigen-deformations in handwritten character recognition
    Uchida, Seiichi
    Ronee, Mohammad Asad
    Sakoe, Hiroaki
    Proceedings - International Conference on Pattern Recognition, 2002, 16 (01): : 572 - 575
  • [39] Interactive Shape Modeling Using Leap Motion Controller
    Cui, Jian
    Sourin, Alexei
    IGGRAPH ASIA 2017 TECHNICAL BRIEFS (SA'17), 2017,
  • [40] Handwritten Assamese Character Recognition
    Sarma, Parismita
    Chourasia, Chandan Kumar
    Barman, Manashjyoti
    2019 IEEE 5TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), 2019,