A method for face identification has been developed by exploiting thermal image processing techniques. The method is based on 2-dimensional detection of the temperature distribution of the face, using infrared rays. The front-view face in the input image is normalized in terms of location and size, followed by measurement of the temperature distribution, the locally averaged temperature and the shape factors of face. The measured temperature distribution and the locally averaged temperature are separately used as input data for a neural network, while the values of shape factors are used for supervised classification. By integrating information from the NN and supervised classification, the face was identified with excellent accuracy. The shortcoming of visible ray image analysis that the accuracy of face identification is strongly influenced by lighting condition including variation of shadow, reflection and darkness is considered to be perfectly overcome by the present method exploiting infrared rays.
[1]
N. Otsu.
A threshold selection method from gray level histograms
,
1979
.
[2]
Yasunari Yoshitomi,et al.
Facial Expression Recognition Using Infrared Rays Image Processing
,
1996
.
[3]
Shigeyuki Tomita,et al.
Facial Expression Recognition Using Thermal Image Processing
,
1997
.
[4]
T. Sakai,et al.
Computer analysis and classification of photographs of human faces
,
1973
.
[5]
L Sirovich,et al.
Low-dimensional procedure for the characterization of human faces.
,
1987,
Journal of the Optical Society of America. A, Optics and image science.
[6]
Alex Pentland,et al.
Face recognition using eigenfaces
,
1991,
Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.