This paper proposes a person identification system (PID), which works with non-illumination low-resolution eye images. Radial-Scan and threshold methods are used for Iris normalization and Iris segmentation from the eye image respectively. Conventional neural network is used for iris matching. The proposed algorithm works with 96 features of the iris. Space complexity is less and Iris codes are...

In this contribution, the vulnerabilities of iris-based recognition systems to direct attacks are studied. A database of fake iris images has been created from real iris of the BioSec baseline database. Iris images are printed using a commercial printer and then, presented at the iris sensor. We use for our experiments a publicly available iris recognition system, which some modifications to im...

Iris recognition has been developing for over 20 years, but, only in recent years has it been more accessible and widely accepted as one of the most accurate and un-obtrusive biometric modalities. Over the past few years, many companies have developed iris acquisition systems that are more user-friendly. Iris-On-the-Move (IOM) is one such system, offering significant stand-off acquisition dista...

Iris recognition is an invasive biometric technique used to identify human being. Iris is defined as annular region between pupil and sclera of human eye which exhibits extraordinary texture that is unique for each individual. Hence, imposes various challenges in accurate iris segmentation and feature extraction techniques to provide many opportunities for researchers in pursuing their research...

For more strict security requirements, biometric research has experienced significant advances in recent years. More important is the need to overcome the rigid constraints necessitated by the practical implementation of sensible but effective security methods such as recognition. An inventive iris acquisition method with less constraints on the iris verification and identification process as w...

Jong-Gook Ko et al. 399 ABSTRACT⎯With a growing emphasis on human identification, iris recognition has recently received increasing attention. Iris recognition includes eye imaging, iris segmentation, verification, and so on. In this letter, we propose a novel and efficient iris recognition method which employs a cumulative-sum-based grey change analysis. Experimental results demonstrate that t...

The face region immediately surrounding one, or both, eyes is called the periocular region. This paper presents an iris segmentation algorithm for challenging periocular images based on a novel iterative ray detection segmentation scheme. Our goal is to convey some of the difficulties in extracting the iris structure in images of the eye characterized by variations in illumination, eye-lid and ...

Iris recognition systems capture an image from an individual’s eye. The iris in the image is then segmented and normalized for feature extraction process. The performance of iris recognition systems highly depends on segmentation and normalization. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented or...