Abstract
Infrared facial images record the temperature-field distribution of facial vein embranchment, which can be regarded as gray features of images. This paper proposes an infrared face recognition algorithm using histogram analysis and K-Nearest Neighbor Classification. Firstly, the irregular facial region of an infrared image is segmented by using the flood-fill algorithm. Secondly, the histogram of this irregular facial region is calculated as the feature of the image. Thirdly, K-Nearest Neighbor is used as a classifier, in which Histogram Matching method and Histogram Intersection method are adopted respectively. Experiments on Equinox Facial Database showed the effectiveness of our approach, which are robust to facial expressions and environment illuminations.
This is a preview of subscription content, log in via an institution to check access.
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
Wu, S., Lin, W., Xie, S.: Skin Heat Transfer Model of Facial Thermograms and Its Application in Face Recognition. Pattern Recognition 41(8), 2718–2729 (2008)
Buddharaju, P., Pavlidis, I.T., Tsiamyrtzis, P., Bazakos, M.: Physiology-Based Face Recognition in the Thermal Infrared Spectrum. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4), 613–626 (2007)
Wu, S.Q., Wei, L.Z., Fang, Z.J., Li, R.W., Ye, X.Q.: Infrared face recognition based on blood perfusion and sub-block DCT in wavelet domain. In: Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2007, pp. 1252–1256 (2007)
Wu, S.Q., Gu, Z.H., Chia, K.A., Ong, S.H.: Infrared Facial Recognition using modified blood perfusion. In: 2007 6th International Conference on Information, Communications and Signal Processing, ICICS, Singapore, pp. 1–5 (2007)
Pavlidis, I., Tsiamyrtzis, P., Manohar, C., Buddharaju, P.: Biometrics: Face Recognition in Thermal Infrared. In: Biomedical Engineering Handbook, February 2006. CRC Press, Boca Raton (2006)
Buddharaju, P., Pavlidis, I., Tsiamyrtzis, P.: Physiology-based face recognition using the vascular network extracted from thermal facial images: a novel approach. In: Proceedings of the IEEE Advanced Video and Signal Based Surveillance, Italy, pp. 354–359 (2005)
Socolinsky, D.A., Selinger, A.: Thermal Face Recognition over Time. In: Proceedings of the Pattern Recognition, 17th International Conference on (ICPR 2004), vol. 4, pp. 187–190 (2004)
Socolinsky, D.A., Selinger, A.: A Comparative Analysis of Face Recognition Performance with Visible and Thermal Infrared Imagery. In: Proc. of ICPR 2002, vol. 4, pp. 217–222 (2002)
Selinger, A., Socolinsky, D.A.: Appearance-Based Facial Recognition Using Visible and Thermal Imagery: A Comparative Study. Equinox Corporation no. 02–01, Technical Report, 2002 (2001)
Prokoski, F.: History, current status, and future of infrared identification. In: Proceedings of IEEE Workshop on Computer Vision beyond the Visible Spectrum: Methods and Applications, pp. 5–14 (2000)
Guyton, A.C., Hall, J.E.: Textbook of Medical Physiology, 9th edn. WB Saunders Company, Philadelphia (1996)
NIST/Equinox Visible and Infrared Face Image Database, http://www.equinoxsensors.com/products/HID.htm
Flood-Fill Algorithm, http://en.wikipedia.org/wiki/Flood_fill
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, S., Liu, Z. (2010). Infrared Face Recognition Based on Histogram and K-Nearest Neighbor Classification. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13318-3_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-13318-3_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13317-6
Online ISBN: 978-3-642-13318-3
eBook Packages: Computer ScienceComputer Science (R0)