Title :
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
fDate :
March 30 2009-April 2 2009
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;
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
DOI :
10.1109/CIB.2009.4925683
