An Implementation of the Korean Sign Language Recognizer Using Neural Network Based on the Post PC

  • Jung-Hyun Kim
  • Kwang-Seok Hong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


A traditional studies about recognition and representation technology of sign language have several restrictions such as conditionality in space and limitation of motion according to the technology of wire communication, problem of image capture system or video processing system for an acquisition of sign language signals, and the sign language recognition system based on word and morpheme. In order to overcome these restrictions and problems, in this paper, we implement the Korean sign language recognizer in the shape of sentence using neural network based on the Post wearable PC platform. The advantages of our approach are as follows: 1) it improves efficiency of the sign language input module according to the technology of wireless communication, 2) it recognizes and represents continuous sign language of users with flexibility in real time, and 3) it is possible more effective and free interchange of ideas and information between deaf person and hearing person (the public). Experimental result shows the average recognition rate of 92.8% about significant, dynamic and continuous the Korean sign language.


Sign Language Gesture Recognition Hand Gesture Sign Language Recognition Average Recognition Rate 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Use of Signs in Hearing Communities,
  2. Jang, H.Y., Kim, D.J., Kim, J.B., Bien, Z.N.: A Study on Hand-Signal Recognition System in 3-Dimensional Space. Journal of IEEK 41, 103–114 (2004)Google Scholar
  3. Kim, S.G.: Standardization of Signed Korean. Journal of KSSE 9 (1992)Google Scholar
  4. Kim, S.G.: Korean Standard Sign Language Tutor. Osung Publishing Company, Seoul (2000)Google Scholar
  5. Kim, J.H., Kim, D.G., Shin, J.H., Lee, S.W., Hong, K.S.: Hand Gesture Recognition System using Fuzzy Algorithm and RDBMS for Post PC. In: Wang, L., Jin, Y. (eds.) FSKD 2005. LNCS (LNAI), vol. 3614, pp. 170–175. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. 5DT Data Glove 5 Manual and FASTRAK® Data Sheet,
  7. Relational DataBase Management System,
  8. Oracle 10g DW Guide,
  9. Simon, H.: Neural Network-A Comprehensive Foundation. Prentice-Hall, Inc., New Jersey (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jung-Hyun Kim
    • 1
  • Kwang-Seok Hong
    • 1
  1. 1.School of Information and Communication EngineeringSungkyunkwan UniversitySuwon, KyungKi-doKorea

Personalised recommendations