@article{(Open Science Index):https://publications.waset.org/pdf/10863,
	  title     = {Similarity Measure Functions for Strategy-Based Biometrics},
	  author    = {Roman V. Yampolskiy and  Venu Govindaraju},
	  country	= {},
	  institution	= {},
	  abstract     = {Functioning of a biometric system in large part
depends on the performance of the similarity measure function.
Frequently a generalized similarity distance measure function such as
Euclidian distance or Mahalanobis distance is applied to the task of
matching biometric feature vectors. However, often accuracy of a
biometric system can be greatly improved by designing a customized
matching algorithm optimized for a particular biometric application.
In this paper we propose a tailored similarity measure function for
behavioral biometric systems based on the expert knowledge of the
feature level data in the domain. We compare performance of a
proposed matching algorithm to that of other well known similarity
distance functions and demonstrate its superiority with respect to the
chosen domain.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {12},
	  year      = {2008},
	  pages     = {4254 - 4259},
	  ee        = {https://publications.waset.org/pdf/10863},
	  url   	= {https://publications.waset.org/vol/24},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 24, 2008},
	}