Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Face Region Detection Using a Variable Ellipsoidal Mask and Morphological Features

가변 타원 마스크와 형태학적 특징을 이용한 얼굴 영역 검출

  • 이재국 (울산대학교 전기전자정보시스템공학부) ;
  • 김경훈 (울산대학교 전기전자정보시스템공학부) ;
  • 김태영 (알칸 대한 주식회사) ;
  • 최원호 (울산대학교 전기전자정보시스템공학부)
  • Published : 2003.05.01
Download PDF
⟨ Previous Next ⟩

Abstract

We propose an algorithm to detect the face region using a variable ellipsoidal mask and a neural network. Since outlines of human faces are similar to ellipsoid, the ellipsoidal mask that has the fixed ratio of major and minor axis can be used to detect the candidate area. The positions of eyes and lips are extracted in this candidate area, and then the morphological analysis is applied to make features which are consist of six parameters, such as the geometrical ratio of eyes and lips. A back-propagation neural network is used as a classifier to determine the most possible face region. The experimental result is conducted to verify its efficiency compared with those of previous works.

Keywords

References

  1. H. W. Lee, S. K. Kil, Y. H. Han, and S. H. Hong, 'Automatic face and facial features detection', Proc. IEEE Int. Symp. on Industrial Electronics, vol. 1, pp. 254-259, Pusan, Korea, 2001 https://doi.org/10.1109/ISIE.2001.931793
  2. C. Lin and K.-C. Fan, 'Human face detection usig geometric triangle relationship', Proc. 15th Int. Conf. on Pattern Recognition, vol. 2, Barcelona, Spain, pp. 941-944, 2000 https://doi.org/10.1109/ICPR.2000.906229
  3. H. Weimin and R. Mariani, 'Face detection and precise eyes location' Proc. 15th Int. Conf. on Pattern Recognition, vol. 4, Barcelona, Spain, pp.722-727, 2000 https://doi.org/10.1109/ICPR.2000.903019
  4. Y.-H. Kwon and N. D. Vitoria Lobo, 'Face detection using templates', Proc. 12th IAPR Int. Conf. on Computer Vision & Image Processing, vol. 1, Jerusalem, Israel, pp. 764-767, 1994 https://doi.org/10.1109/ICPR.1994.576435
  5. K. K. Sung and T. Poggio, 'Example based learning for view-based human face detection', IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 20, 1998 https://doi.org/10.1109/34.655648
  6. E. Saber and A. M. Tekalp, 'Face detection and facial feature extraction using color, shape and symmetry-based cost functions,' Proc. 13th Int. Conf. on Pattern Recognitionvol. 3, Vienna, Austria, pp. 654-658, 1996 https://doi.org/10.1109/ICPR.1996.547027
  7. R. Feraund, O. J. Bernier, J.-E. Viallet, and M. Collobert, 'A fast and accurate face detector based on neural networks', IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 23, pp. 42-53, 2001 https://doi.org/10.1109/34.899945
  8. H. A. Rowley, S. Baluja, and T. Kanade, 'Neural network-based face detection', IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 20, pp. 23-38, 1998 https://doi.org/10.1109/34.655647
  9. J. Canny, 'A computational approach to edge detection', IEEE Trans. on Patten Analysis and Machine Intelligence, vol. 8, no. 6, 1986
  10. http://www.bioid.com/downloads/facedb/
  11. O. Jesorsky, K. Kirchberg, and R. Frischholz, 'Robust face detection using the hausdorff distance', Proc. 3th Int. Conf. on Audio and Video based Biometric Person Authentication, Halmstad,Sweden, pp.90-95, 2001
  12. B. Froba and C. Kublbeck, 'Robust face detection at video frame rate based on edge orientation features', Proc. 5th IEEE Int. Conf. on Automatic Face and Gesture Recognition, Washington, U.S.A., pp. 342-347, 2002 https://doi.org/10.1109/AFGR.2002.1004177