Iris recognition is an automated method of biometric identification, taking unique patterns within a ring-shaped region surrounding the pupil of each eye. It is an extremely reliable and accurate identification method with very low false match rates. However, it has some disadvantages such as requiring specialized hardware equipment.
The history of iris recognition is relatively young. It all began in 1936 when ophthalmologist Frank Burch identified differences between human irises and proposed the patterns as a method to recognize individuals. However, it was not until 1987 when doctors, Leonard Flam and Aran Safir, were awarded a patent for the iris identification concept, based on the idea that no two irises are the same. The upswing of iris recognition as an identification method came just after the millennium when patents expired and the technology was ready for broad commercialization.
Iris scanning illuminates irises with invisible infrared light to take a picture of unique patterns in each eye, not visible to the naked eye. A special camera takes the position of the pupil, iris, eyelids and eyelashes. Each eye gets its own unique mathematical patterns, which is further digitized.
For identification (1:N) or verification (1:1), a template created by imaging an iris is compared to the stored template in a database.
The National Institute of Standards and Technology (NIST) is the leading international biometric testing organization and industry-standard developer. NIST is actively involved in developing architectures and conformance test tools to support users that need to comply with selected biometric standards and support product developers and testing laboratories interested in conforming to biometric standards by using the same testing tools available. NIST evaluates iris recognition algorithms in NIST testing: