Human Identification System Based on PCA Using Geometric Features of Teeth
We present a new human identification system based on PCA using geometric features of teeth such as the size and shape of the jaws, size of the teeth and teeth structure. In this paper we try to set forth the foundations of a biometric system for information encrypting of living people using dental features. To create a biometric matching system, a template based on principal component analysis(PCA) is created from dental data collected the plaster figures of teeth which were done at dental hospital, department of oral medicine. Templates of dental images based on PCA representation include the 100 principle components as the features for individual identification. The PCA basis vectors reflects well the features for individual identification in the whole of teeth and the part of teeth. The classification for human identification is generated based on the distance between the whole of teeth and the part of teeth with the nearest neighbor(NN) algorithm. The identification performance in 300 dental image is 97% for the part of teeth missed the right-molar and back teeth, 98.3% for the part of teeth missed the front teeth and 96.6% for the part of teeth missed the left-molar and back-teeth.
KeywordsRecognition Rate Near Neighbor Individual Identification Biometric System Tooth Structure
- 2.Phillips, P.J.: Support vector machines applied to face recognition, Technical Report, NISTIR 6241, National Institute of Standards and Technology (1999)Google Scholar
- 4.Jain, A.K., Ross, A., Pankanti, S.: A prototype hand geometry-based verification system. In: Second International Conf. on Audio and Video-based Biometric Person Authentification, Washington DC, USA (March 1999)Google Scholar
- 5.Furui, S.: Recent advances in speaker recognition. In: Bigun, J., Borgeford, G. (eds.) Audio and Video-based Biometric Person Authentification. Springer, Berlin (1997)Google Scholar
- 9.Cottrell, G., Metcalfe, J.: Face, gender and emotion recognition using holons. In: Touretzky, D. (ed.) Advances in Neural information processing systems(3), San Maleo, CA, pp. 564–571. Morgan Kaufmann, San Francisco (1991)Google Scholar