Abstract
The localization of the iris is the most significant factor in biometrics of the iris, which traditionally assumes strictly controlled environments. The proposed method includes the pupillary and limbic iris boundaries localization. A primary advantage of image arithmetic operations is that the process is straightforward and therefore fast, these characteristics are employed and combined with the morphological operators in the designing of the proposed algorithm. The proposed algorithm takes into account the noise area which is found in various parts of the eye image such as light reflections, focus, and small visible iris. The experimental results are conducted on a collection of iris images consist of 756 images belong to Chinese Academy of Sciences Institute of Automation (CASIA V-1) and 450 images belong to Multi Media University (MMU V-1) databases. The results indicate a high level of accuracy using the proposed technique. Moreover, the comparison results with the state-of-the-art iris localization algorithms expose considerable improvement in segmentation accuracy while being computationally more efficient.
Highlights
For the automated personal identification, iris recognition is one of the most accurate and broadly employed methodology
Traditional iris localization methods and matching features depend only on near-infrared illumination and require samples to be taken under strictly restricted conditions [2], which is the main difficulty of deploying an iris recognition system in civilian and surveillance applications
Another threshold was required in the proposed method for iris localization, which was selected depending on the statistical relationships between of the original image and the image after thresholding with a small value to preserve only the dark pixels
Summary
For the automated personal identification, iris recognition is one of the most accurate and broadly employed methodology. A typical iris recognition system comprises segmentation, normalisation, feature extraction and matching. Traditional iris localization methods and matching features depend only on near-infrared illumination and require samples to be taken under strictly restricted conditions [2], which is the main difficulty of deploying an iris recognition system in civilian and surveillance applications. The proposed method was designed to take the advantage of the image arithmetic operations features with morphological operators features for localizing the iris. This paper is organised as follows: Section 2 overviews the existing literature for iris localization.
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