Overview
Personal recognition is the process of determining the identity of a particular individual from a database of known people. Recognizing someone’s identity has been a concern of modern societies now that the restriction of access to data is crucial in almost every contemporary field, mostly due to fraud attempts and other illegal attacks. The most frequent recognition applications are the ones used for criminal investigation, access to security systems or restricted areas, border control and access to computers or cellphones.
The traditional way of validating one’s identity is by using something that can be possessed or learnt, as a magnetic card, Radio-Frequency Identification (RFID) card or a password. However, as items and keys can be lost, stolen, forgotten or revealed, enabling fraudulent usage, it is known that a more reliable way of recognition is by using something that one is, instead of something that one has or knows.
For this reason, it is becoming conventional the application of biometrics in recognition systems. This phenomenon is arising due to the fact that biometrics recognition systems operate based on physical or behavioral features, called biometric traits, which are usually exclusive of each person.
A biometric recognition system can use one or several human traits as samples, being the most commonly adopted the fingerprint, the speech, the face, the iris or the retina.
The fingerprint is the most known biometric trait used in recognition systems and it is still the most used one due to its easiness of acquisition, high distinctiveness, persistence, and acceptance by the users.
On the other hand, iris recognition is increasingly employed in admission systems and it is constantly evolving. It has been considered as one of the strongest recognition methods due to the characteristics of the human iris, which are usually exclusive to a singular individual.
The fact that the iris is such an exclusive human feature becomes a huge advantage when used in recognition systems. However, contrary to what was believed to be true, recent researches conclude that the aging of an iris template is possible and it leads to the increment of the error rate between an enrollment image and an image taken for the recognition process, a few years after.