Abstract
Biometrics is a method of identifying individuals by their physiological or behavioral characteristics. Among other biometric identifiers, iris recognition has been widely used for various applications that require a high level of security. When a conventional iris recognition camera is used, the size and position of the iris region in a captured image vary according to the X , Y positions of a user’s eye and the Z distance between a user and the camera. Therefore, the searching area of the iris detection algorithm is increased, which can inevitably decrease both the detection speed and accuracy. To solve these problems, we propose a new method of iris localization that uses wide field of view (WFOV) and narrow field of view (NFOV) cameras. Our study is new as compared to previous studies in the following four ways. First, the device used in our research acquires three images, one each of the face and both irises, using one WFOV and two NFOV cameras simultaneously. The relation between the WFOV and NFOV cameras is determined by simple geometric transformation without complex calibration. Second, the Z distance (between a user’s eye and the iris camera) is estimated based on the iris size in the WFOV image and anthropometric data of the size of the human iris. Third, the accuracy of the geometric transformation between the WFOV and NFOV cameras is enhanced by using multiple matrices of the transformation according to the Z distance. Fourth, the searching region for iris localization in the NFOV image is significantly reduced based on the detected iris region in the WFOV image and the matrix of geometric transformation corresponding to the estimated Z distance. Experimental results showed that the performance of the proposed iris localization method is better than that of conventional methods in terms of accuracy and processing time.
Highlights
With the increasing security requirements of the current information society, personal identification is becoming increasingly important
Iris recognition means identifying a person based on the unique iris pattern that exists in the iris region between the sclera and the pupil
We proposed a new method for enhancing the performance of iris localization based on wide field of view (WFOV) and narrow field of view (NFOV) cameras
Summary
With the increasing security requirements of the current information society, personal identification is becoming increasingly important. Conventional methods for the identification of an individual include possession-based methods that use specific things (such as smart cards, keys, tokens) and knowledge-based methods that use what the individual knows (such as a password or a PIN) These methods have the disadvantages that tokens and passwords can be shared, misplaced, duplicated, lost, or forgotten.[1] over the last few decades, a new method called biometrics has been attracting attention as a promising identification technology. This technique uses a person’s physiological or behavioral traits, such as the iris, face, fingerprint, gait, or voice.[4] In particular, iris recognition means identifying a person based on the unique iris pattern that exists in the iris region between the sclera and the pupil. There are two major approaches for iris localization,[6] one of which is based on circular edge detection (CED), such as the Hough transform, and the other on histograms
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