Many researchers have studied iris recognition techniques in unconstrained environments, where the probability of acquiring non-ideal iris images is very high due to off-angles, noise, blurring and occlusion by eyelashes, eyelids, glasses, and hair. Although there have been many iris segmentation methods, most focus primarily on the accurate detection with iris images which are captured in a cl...

The demand for an accurate biometric system that provides reliable identification and verification of an individual has increased over the years. A biometric system that provides reliable and accurate identification of an individual is an iris recognition system. In which paper describes the segmentation and the normalization processing for biometric iris recognition system, implemented and val...

Iris segmentation is an essential module in iris recognition because it defines the effective image region used for subsequent processing such as feature extraction. Traditional iris segmentation methods often involve an exhaustive search of a large parameter space, which is time-consuming and sensitive to noise. To address these problems, this paper presents a novel algorithm for accurate and ...

The use of biometric signatures, instead of tokens such as identification cards or computer passwords, continues to gain increasing attention as an efficient means of identification and verification of individuals for controlling access to secured areas, materials, or systems and a wide variety of biometrics has been considered over the years in support of these challenges. Iris recognition is ...

Iris recognition is one of the most reliable and accurate biometric technologies, as the richness and apparent stability of the iris texture make it robust. Iris segmentation is a critical part in iris recognition, because it defines the inner and outer boundaries of iris region which is used for feature analysis. Active contour model, also known as snake, is a powerful image segmentation techn...

Pupil segmentation is usually the first step used for searching iris regions. Iris localization is an extremely important procedure in iris biometrics systems, since the correct segmentation of inner and outer boundaries is critical to achieve high recognition rates. An iris localization method based on a spring force-driven iterative scheme, called Pulling & Pushing have been proposed by He et...

With the development of the current networked society, personal identification based on biometrics has received more and more attention. Iris recognition has a satisfying performance due to its high reliability and non-invasion. In an iris recognition system, preprocessing, especially iris localization plays a very important role. The speed and performance of an iris recognition system is cruci...

This paper proposes an iris image quality and segmentation accuracy evaluation method for videobased iris recognition systems, operating in unconstrained environment. Proposed approach consists of two stages of video quality evaluation that allows improving the iris recognition rates in non-ideal or no cooperative situations; where the first stage discards the low quality eye frames, while the ...

An overview of the iris image segmentation methodologies for biometric purposes is presented. The main focus is on the analysis of the ability of segmentation algorithms to process images with heterogeneous characteristics, simulating the dynamics of a non-cooperative environment. The accuracy of the four selected methodologies on the UBIRIS database is tested and, having concluded about their ...

This paper presents a new iris database that contains images with noise. This is in contrast with the existing databases, that are noise free. UBIRIS is a tool for the development of robust iris recognition algorithms for biometric proposes. We present a detailed description of the many characteristics of UBIRIS and a comparison of several image segmentation approaches used in the current iris ...