Minimizing the number of bits needed for iris recognition via Bit Inconsistency and GRIT

Author

Dozier, Gerry ; Frederiksen, Kurt ; Meeks, Robert ; Savvides, Marios ; Bryant, Kelvin ; Hopes, Darlene ; Munemoto, Taihei

Author_Institution

Center of Acad. Studies in Identity Sci. (CASIS), Dept. of Comput. Sci., North Carolina A&T State Univ., Greensboro, NC

fYear

2009

fDate

March 30 2009-April 2 2009

Firstpage

30

Lastpage

37

Abstract

In this paper, we demonstrate how the concepts of bit inconsistency and genetic search can be used to minimize the number of iris code bits needed for iris recognition. In addition, we compare two systems: GRIT-I (genetically refined iris templates I) and GRIT-II. Our results show that GRIT-I (by evolving the bit mask of iris templates) was able to reduce the number of iris code bits needed by approximately 30% on average. GRIT-II by contrast optimizes the bit mask as well as the iris code bits that have 100% consistency and 100% coverage with respect to the training set. GRIT-II was able to reduce the number of iris code bits needed by approximately 89%.

Keywords

biometrics (access control); image recognition; bit inconsistency; genetic search; genetically refined iris templates; iris recognition; Eyelashes; Eyelids; Genetic algorithms; Helium; Image analysis; Iris recognition; Kelvin; Machine learning; Predictive models; Probability distribution;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Biometrics: Theory, Algorithms, and Applications, 2009. CIB 2009. IEEE Workshop on

Conference_Location

Nashville, TN

Print_ISBN

978-1-4244-2773-4

Type

conf

DOI

10.1109/CIB.2009.4925683

Filename

4925683