The Journal of the Korea Contents Association (한국콘텐츠학회논문지)

The Korea Contents Association (한국콘텐츠학회)
권호 표지
DOI QR코드

DOI QR Code

Color Area Correction Algorithm for Tracking Curved Fingertip

구부러진 손가락 끝점 추적을 위한 컬러 영역 보정 알고리즘

  • 강성관 (인하대학교 정보공학과) ;
  • 정경용 (상지대학교 컴퓨터정보공학부) ;
  • 임기욱 (선문대학교 컴퓨터정보공학부) ;
  • 이정현 (인하대학교 컴퓨터정보공학부)
  • Received : 2011.07.07
  • Accepted : 2011.07.28
  • Published : 2011.10.28
Download PDF
⟨ Previous Next ⟩

Abstract

In the field of image processing to track the fingertip much research has been done. The most common way to calculate the fingertip first, to extract color information. Then, it uses Blob Coloring algorithms which are expressed in blob functions the skin contour and calculates. The algorithm from contour decides the highest location with the fingertip. But this method when measuring it location from the finger condition which bents is not the actual fingertip and has the problem which detects the location which goes wrong. This paper proposes the color space correction algorithm to tracks the fingertip which bents. The method which proposes when tracking the fingertip from the finger condition which bents solves the problem which measures the location which goes wrong. Aim of this paper in compliance with the propensity of the users forecasts a problem in advance and corrects with improvement at the time of height boil an efficiency. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the satisfaction and the quality of services will be improved the image recognition.

기존 손가락 추적을 수행하는데 있어 손가락 끝점을 계산하는 방법 중 가장 일반적인 방법은 먼저 피부색정보를 추출한다. 블럽 함수의 블럽 컬러링(Blob Coloring) 알고리즘을 통하여 피부 윤곽선을 계산하고, 그 중 가장 최상위 점을 손가락 끝점으로 정한다. 그러나 이 방법은 구부러진 손가락 상태에서 그것의 위치를 측정할 때 실제 손가락 끝이 아닌 잘못된 위치를 탐지하는 문제점을 가지고 있다. 본 논문에서는 구부러진 손가락 끝점 추적을 위한 컬러 영역 보정 알고리즘을 제안하였다. 제안하는 방법은 구부러진 손가락 상태에서의 손가락 끝점 추적시 잘못된 곳을 측정하는 문제점을 사용자들의 성향을 통해 미리 예상하고 보정함으로써 성능을 향상시키고자 한다. 제안하는 방법을 개발하여 논리적 타당성과 유효성을 검증하기 위해 실험적인 적용을 시도하고자 한다. 따라서 영상인식에서 서비스의 만족도와 질을 향상시켰다.

Keywords

References

  1. T. Brown and R C. Thomas, "Finger Tracking for the Ditgital Desk," In Proc. of the Australasian User Interface Conference, pp.11-16, 2000.
  2. A. M. Bowden and R. Bowden, "View-based Location and Tracking of Body Parts for Visual Interaction," In BMVA Symposium on Spatiotemporal Image Processing, 2004.
  3. 임옥현, 김진철, 박성미, 이배호, "블럽 컬러 링을 이용한 CT 영상에서 간 영역 자동 추출", 한국정보과학회, 제31권, 제2호, pp.760-762, 2004.
  4. S. Tsuruoka, A. Kinoshita, T. Wakabayashi, and Y. M. Ishida, "Extraction of Hand Region and Spectification of Fingertips from Color Image," In Proc. of International Conference Virtual Systems and Multimedia, pp.206-211, 1997.
  5. R. Hota, V. Venkoparao, and S. Bedros, "Face Detection by using Skin Color Model based on One Class Classifier," In Proc. of International Conference on Information Technology, pp.15-16, 2006. https://doi.org/10.1109/ICIT.2006.54
  6. F. Javier, Toledo-Moreo, J. J. Martinez-Alvarez, and J. M. Ferrandez-Vicente, "Hand-based Interface for Augmented Reality," In Proc. of IEEE Symposium on Field-Programmable Custom Computing Machines, pp,291-292, 2007. https://doi.org/10.1109/FCCM.2007.24
  7. F. Boussaid, D Chai, and A. Bouzerdoum, "On-Chip Skin Detection for Color CMOS Imagers," In Proc. of International Conference on MEMS, NSNO and Smart System, pp.357-361, 2003. https://doi.org/10.1109/ICMENS.2003.1222024
  8. B. A. Meza, M. Nagarajan, C. Ramakrishnan, L. Ding, P. Kolari, A. P. Sheth, I. B. Arpinar, A. Joshi, and T. Finin, "Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection," In Proc. of the International Conference on World Wide Web, 2006.
  9. K. Oka, Y. Satoand, and H. Koike, "Real-time Tracking of Multiple Fingertips and Gesture Recognition for Augmented Desk Interface Systems," In Proc. of International Conference on Automatic Face and Gesture Recognition, pp.411-416, 2002.
  10. H. Fillbrandt, S. Akyol, and K. F. Kraiss, "Extraction of 3D Hand Shape and Posture from Image Sequences for Sign Language Recognition," IEEE International Workshop on Analysis and Modeling of Faces and Gestures, Vol.17, No.10, pp.181-186, 2003. https://doi.org/10.1109/AMFG.2003.1240841
  11. W. Z. Gang, and Z. D. Fang1, "Application of Visualization Technology in Spatial Data Mining," Computer Engineering, Vol.33, No.18, pp.67-71, 2009.
  12. Z. Jin. Visualization for Information Retrieval, Springer, 2008.
  13. A. Jaimes and N. Sebe, "Multimodal Human Computer Interaction: A Survey," Computer Vision and Image Understanding, Vol.108, Issue1-2, pp.116-134, 2007. https://doi.org/10.1016/j.cviu.2006.10.019
  14. M. Cabral, M. Zuffo, S. Ghirotti, O. Belloc, L. Nomura, M. Nagamura, F. Andrade, R. Faria, and L Ferraz, "An Experience using X3D for Virtual Cultural Heritage," In Proc. of the Int. Conference on 3D Web Technology, pp.161-164, 2007.
  15. K. Y. Jung and J. H. Lee, "User Preference Mining through Hybrid Collaborative Filtering and Content-based Filtering in Recommendation System," IEICE Tran. on Information and Systems, Vol.E87-D, No.12, pp.2781-2790, 2004.
  16. P. A. Chirita, A. Damian, W. Nejdi and W. Siberski, "Search Strategies for Scientific Collaboration Networks," In Proc. of the ACM Workshop on Information Retrieval in Peer-to-Peer Networks, 2005.

Cited by

  1. Sequential pattern profiling based bio-detection for smart health service vol.18, pp.1, 2015, https://doi.org/10.1007/s10586-014-0370-3