Iris Recognition System with Accurate Eyelash Segmentation and Improved FAR, FRR using Textural and Topological Features

s paper represents novel iris recognition technique which uses textural and topological features. Converting circular iris pattern into rectangular pattern makes it rotation invariant. Most of the research in iris recognition is on encoding and recognition of iris pattern but segmenting exact iris pattern is itself very tedious task in this paper we are trying to emphasize on better iris segmentation technique . In other systems performance of the system is always dependent on threshold. There is always conflict between FAR & FRR, if tied to improve one quantity degrades other one. This paper describes an alternate means to identify individuals using images of their iris with low false acceptance rate and low false rejection rate. For encoding topological feature Euler vector can be utilized while for encoding textural feature histogram is used. Histogram is matched by using Du measure whose origin belong in Hyperspectral Image Analysis while for matching euler vector Vector Difference Matching algorithm is developed . KeywordsDu measure, Euler vector, FAR, FRR