Abstract
This paper assesses the usefulness of color information for face recognition tasks. Experimental results using the FERET database show that color information improves performance for detecting and locating eyes and faces, respectively, and that there is no significant difference in recognition accuracy between full color and gray-scale face imagery. Our experiments have also shown that the eigenvectors generated by the red channel lead to improved performance against the eigenvectors generated from all the other monochromatic channels. The probable reason for this observation is that in the near infrared portion of the electro-magnetic spectrum, the face is least sensitive to changes in illumination. As a consequence it seems that the color space as a whole does not improve performance on face recognition but that when one considers monochrome channels on their own the red channel could benefit both learning the eigenspace and serving as input to project on it.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Samal, A. and Iyengar, P.: Automatic Recognition and Analysis of Human Faces and Facial Expressions-A Survey. Pattern Recognition 25 (1992) 65–77.
Kemp, R, Pike, G., White, P., and Musselman, A.: Perception and Recognition of Normal and Negative Faces-The Role of Shape from Shading and Pigmentation Cues. Perception 25 (1996) 37–52.
Philips P.J., Wechsler, H., Huang, J., and Rauss, P.: The FERET Database and Evaluation Procedure for Face Recognition Algorithms.J.Image Vision Comp. 16(5) (1998) 295–306.
Quinlan, J.R.: C4.5-Programs for Machine Learning, Morgan Kaufmann (1993).
Haykin, S.: Neural Networks, Maxmillan Publishing Company (1999).
Kirby, M. and Sirovich, L.: Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces. IEEE Trans. PAMI. Intel. 12(1) 1990 103–108.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gutta, S., Huang, J., Liu, C., Wechsler, H. (2001). Comparative Performance Evaluation of Gray-Scale and Color Information for Face Recognition Tasks. In: Bigun, J., Smeraldi, F. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2001. Lecture Notes in Computer Science, vol 2091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45344-X_6
Download citation
DOI: https://doi.org/10.1007/3-540-45344-X_6
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42216-7
Online ISBN: 978-3-540-45344-4
eBook Packages: Springer Book Archive