Abstract
Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.
Highlights
Biometric features are unique identifying characteristics of an individual which are more convenient and secure than traditional authentication methods
Retinal identification based on retinal vasculatures provides the most secure and accurate authentication means among biometrics
We have presented a robust retinal identification method based on Scale Invariant Feature Transform (SIFT) and Improved Circular Gabor Transform (ICGF)
Summary
Biometric features are unique identifying characteristics of an individual which are more convenient and secure than traditional authentication methods. Biometrics or biometric authentication [1,2], refers to automated methods of recognizing a person using behavioral or physiological features, such as faces [3], gaits [4], fingerprints [5,6], irises [7], veins [8], etc Among these features, the retina may provide a higher level of security due to its inherent robustness against imposters. A new retinal identification method based on SIFT and ICGF is presented. A new approach based on ICGF is proposed for enhancing the details of retinal images, and the background is uniformed simultaneously.
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