Hand-Gesture Recognition Using Concentric-Circle Expanding and Tracing Algorithm

동심원 확장 및 추적 알고리즘을 이용한 손동작 인식

  • Hwang, Dong-Hyun (School of Computer Science and Engineering, Korea University of Technology and Education) ;
  • Jang, Kyung-Sik (School of Computer Science and Engineering, Korea University of Technology and Education)
  • Received : 2016.10.11
  • Accepted : 2016.10.31
  • Published : 2017.03.31


In this paper, We proposed a novel hand-gesture recognition algorithm using concentric-circle expanding and tracing. The proposed algorithm determines region of interest of hand image through preprocessing the original image acquired by web-camera and extracts the feature of hand gesture such as the number of stretched fingers, finger tips and finger bases, angle between the fingers which can be used as intuitive method for of human computer interaction. The proposed algorithm also reduces computational complexity compared with raster scan method through referencing only pixels of concentric-circles. The experimental result shows that the 9 hand gestures can be recognized with an average accuracy of 90.7% and an average algorithm execution time is 78ms. The algorithm is confirmed as a feasible way to a useful input method for virtual reality, augmented reality, mixed reality and perceptual interfaces of human computer interaction.

본 논문은 동심원 확장 및 추적 기법을 이용하여 손동작을 인식하는 알고리즘을 제안한다. 제안하는 알고리즘은 웹 카메라로부터 영상을 입력받아 전처리 과정을 통해 손 영상에 대한 ROI를 추출한 뒤 동심원을 사용하여 펴진 손가락의 개수뿐만 아니라 손가락의 끝점, 손가락의 기저의 위치정보, 손가락 사이의 각도를 추출하여 HCI분야에서 활용할 수 있는 다양한 입력 방법을 제공한다. 또한 이 알고리즘은 이미지 전체의 화소를 참조하는 래스터 스캔방식과 비교하여 동심원을 구성하는 화소만을 참조함으로서 계산복잡도를 줄일 수 있다. 제안하는 알고리즘은 9가지의 손동작을 평균 90.7%의 인식률과 평균 78ms의 수행속도를 보여줌을 확인했고, 가상현실, 증강현실 및 혼합현실 그리고 HCI 분야 전반의 입력수단으로의 적용가능성을 확인하였다.



  1. D. H. Hwang, K. S. Jang, "Finger-Gesture Recognition Using Concentric-Circle Tracing Algorithm," Journal of Korea Institute of Information and Communication Engineering, vol. 19, no. 12, pp. 2956-2962, Dec. 2015.
  2. K. Oka, Y. Sato, and H. Koike, "Real-time fingertip tracking and gesture recognition," IEEE Computer graphics and Applications, vol. 22, no. 6, pp. 64-71, Nov. 2002.
  3. P, Singh, R. S. Lodhi, "Hand tracking and head movement detection: A State-of-Art Survey," International Journal of Computer and Advanced Engineering Research, vol. 1, no. 2, pp. 12-16, Aug. 2014.
  4. S. Nagarajan, T. S. Subashini, and V. Ramalingam, "Vision based real time finger counter for hand gesture recognition," International Journal of Technology, vol. 2. no. 2, pp. 1-5, Dec. 2012.
  5. A. Malima, E. Ozgur, and M. Cetin, "A fast algorithm for vision-based hand gesture recognition for robot control," in Proceedings of the IEEE 14th Signal Processing and Communications Applications, Antalya: TR, 2006.
  6. A. R. Sarkar, G. Sanyal, and S. Majumder, "Hand gesture recognition systems: a survey," International Journal of Computer Applications, vol. 71, no. 15, pp. 26-37, May 2013.
  7. S. C. Ji, S. W. Kang, J. S. Kim and H. Joo, "The Development of a Real-Time Hand Gestures Recognition System Using Infrared Images," Journal of Institute of Control, Robotics and Systems, vol. 21, no. 12, pp. 1100- 1108, Dec. 2015.
  8. S. K. Singh, D. S. Chauhan, M. Vasta, and R. Singh, "A robust skin color based face detection algorithm," Tamkang Journal of Science and Engineering, vol. 6, no. 4, pp. 227- 234, Dec. 2003.
  9. W. T. Freeman, et al, "Computer vision for interactive computer graphics," IEEE Computer Graphics and Applications, vol. 18, no. 3, pp. 42-53, May 1998.

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