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http://dx.doi.org/10.5391/JKIIS.2004.14.7.821

Robust Real-time Face Detection Scheme on Various illumination Conditions  

Kim, Soo-Hyun (숭실대학교 정보통신전자공학부)
Han, Young-Joon (숭실대학교 정보통신전자공학부)
Cha, Hyung-Tai (숭실대학교 정보통신전자공학부)
Hahn, Hern-Soo (숭실대학교 정보통신전자공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.14, no.7, 2004 , pp. 821-829 More about this Journal
Abstract
A face recognition has been used for verifying and authorizing valid users, but its applications have been restricted according to lighting conditions. In order to minimizing the restricted conditions, this paper proposes a new algorithm of detecting the face from the input image obtained under the irregular lighting condition. First, the proposed algorithm extracts an edge difference image from the input image where a skin color and a face contour are disappeared due to the background color or the lighting direction. In the next step, it extracts a face region using the histogram of the edge difference image and the intensity information. Using the intensity information, the face region is divided into the horizontal regions with feasible facial features. The each of horizontal regions is classified as three groups with the facial features(including eye, nose, and mouth) and the facial features are extracted using empirical properties of the facial features. Only when the facial features satisfy their topological rules, the face region is considered as a face. It has been proved by the experiments that the proposed algorithm can detect faces even when the large portion of face contour is lost due to the inadequate lighting condition or the image background color is similar to the skin color.
Keywords
Face detection; Edge detection; Facial features; Various lighting conditions;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 C. Kotropoulos and I. Pitas, 'Rule-based Face Detection in Frontal Views,' Proc. IEEE Int'l Conf. on Acoustics, Speech and Signal Processing, Vol. 4, pp. 2537-2530, 1997
2 S. Kim, S. Lim, H. Cha and H. Hahn, 'Block Based Face Detection Scheme Using Face Color and Motion Information,' 퍼지 및 시스템 학회 논문지, 제 13권, 4호, pp. 461-468, 2003년 8월   DOI
3 P. Sinha, 'Object recognition via image invariants: A case study,' Investigative Ophthalmology and Visual Science, Vol. 35, pp. 1735-1740, May 1994
4 H. A. Rowley, S. Baluja, and T. Kanade, 'Neural network-based face detection,' IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 20, No.1, pp. 23-38, Jan. 1998   DOI   ScienceOn
5 P. Remagnino, G. A. Jones, N. Paragios and C. S. Regazzoni, Video-based Surveillance Systems Comuter vision and Distributed Processing, Kluwer, 2002
6 T. Yokoyama, Y. Yagi and M. Yachida, 'Facial contour extraction model,' IEEE Proc, of 3rd Int'l Conf. on Automatic Face and Gesture Recognition, 1998
7 K. C. Yow and R. Cipolla, 'Feature-Based Human Face Detection,' Technical Report CLJED/INFENG/ TR249, University of Cambridge, Aug. 1996
8 H. Rein-Lien, M. Abdel-Mottaleb, and A. K. Jain, 'Face detection in Color Images,' IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 24, No.5, pp. 696-706, May 2002   DOI   ScienceOn
9 H. Zhao and Y. Huang, 'Real-Time Multiple-Person Tracking System,' , Vol. 2, pp. 879-900, 2002
10 I. Pitas, Digital Image Processing Algorithms and Applications, Wiley-Interscience, 2000