Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지
DOI QR코드

DOI QR Code

Robust Pupil Detection using Rank Order Filter and Cross-Correlation

Rank Order Filter와 상호상관을 이용한 강인한 눈동자 검출

  • Jang, Kyung-Shik (Department of multimedia Engineering, Dongeui University) ;
  • Park, Sung-Dae (Department of Digital Contents Engineering, Dongeui University)
  • Received : 2013.03.27
  • Accepted : 2013.04.17
  • Published : 2013.07.31
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we propose a robust pupil detection method using rank order filter and cross-correlation. Potential pupil candidates are detected using rank order filter. Eye region is binarized using variable threshold to find eyebrow, and pupil candidates at the eyebrow are removed. The positions of pupil candidates are corrected, the pupil candidates are grouped into pairs based on geometric constraints. A similarity measure is obtained for two eye of each pair using cross-correlation, we select a pair with the largest similarity measure as a final pupil. The experiments have been performed for 500 images of the BioID face database. The results show that it achieves the high detection rate of 96.8% and improves about 11.6% than existing method.

이 논문에서는 rank order 필터와 상호상관을 이용하여 강인하게 눈동자를 찾는 방법을 제안한다. rank order 필터를 사용하여 얼굴 영상에서 눈동자 후보점을 찾는다. 임계치를 변화하며 눈 영역을 이진화하여 눈썹 위치를 구한 후 눈썹 영역의 눈동자 후보점을 제거한다. 눈동자 위치를 보정한 후 두 눈동자 후보점을 기하학적인 제약조건을 기반으로 쌍으로 묶는다. 각 쌍의 두 눈에 대한 유사도를 상호상관을 이용하여 측정하여 가장 큰 값을 갖는 쌍을 최종 눈동자로 결정한다. BioID 얼굴 데이터베이스의 얼굴 영상 500개에 대한 실험 결과 96.8%의 높은 눈동자 검출율을 보였으며 기존 방법보다 약 11.6% 개선된 결과를 얻었다.

Keywords

References

  1. Dan Witzner Hansen and Qiang Ji, "In the Eye of the Beholder: A Survey of Models for Eyes and Gaze," IEEE Trans. on PAMI, vol. 32, no. 3, pp. 478-497, Mar. 2010. https://doi.org/10.1109/TPAMI.2009.30
  2. Zeynep Orman, Abdulkadir Battal and Erdem Kemer, "A Study on Face, Eye Detection and Gaze Estimation," Int. J. of Computer Science & Engineering Survey, vol. 2, no. 3, pp 29-46, Aug. 2010.
  3. A.L. Yuille, P.W. Hallinan, D.S. Cohen, "Feature extraction from faces using deformable templates", Int. J. Computer Vision, vol. 8, pp. 99-111, Aug. 1992. https://doi.org/10.1007/BF00127169
  4. Fei Zuo, Peter H.N. de With. "Real-time Face Detection and Feature Localization for Consumer Applications," in Proceedings of the PROGRESS/STW, pp.257-262, 2003.
  5. Jurgen Rurainsky, Peter Eisert, "Template-Based Eye and Mouth Detection for 3D Video Conferencing," LNCS, vol. 2849, pp.23-31, 2003.
  6. T. Akashi, Y. Wakasa, K. Tanaka, S. G. Karungaru, and M. Fukumi, "Genetic eye detection using artificial template," Journal of Signal Processing, vol. 10, no. 6, pp. 453-463, November 2006.
  7. Nishimura, T. Nakashige, M. Akashi, T. Wakasa, Y. Tanaka, K "Eye interface for physically impaired people by Genetic Eye Tracking,"in SICE Annual Conference 2007, pp. 17-20, 2007.
  8. Z. Zhou and X. Geng, "Projection Functions for Eye Detection," Pattern Recognition, vol. 37, no. 5, pp. 1049-1056, May 2004. https://doi.org/10.1016/j.patcog.2003.09.006
  9. Zhifei Xu and Pengfei Shi, "A Robust and Accurate Method for Pupil Features Extraction," in Proceedings of Int. Conf. on Pattern Recongnition, pp.437-440, 2006.
  10. Jianfeng, Ren, "Eye Detection Based on Rank Order Filter," in Proceedings of Int. Conf. on Information, Communications and Signal Processing, pp. 1-4, 2009.
  11. Ling Gan and Qingjun Liu, "Eye Detection Based on Rank Order Filter and Projection Function," in Int. Conf. On Computer Design and Application, pp. 642-645, 2010.
  12. O. Jesprsky, K. Kirchberg, R. Frischholz,"Robust Face Detection Using the Hausdorff Distance," in Proceedings of Int. Conf. on Audio based Person Authentication - AVBPA, pp90-95, 2001.