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

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%.