We present a new iris segmentation algorithm based on the Generalized Structure Tensor (GST). We compare this approach with traditional iris segmentation systems based on Hough transform and integro-differential operators. Results are given using the CASIA-IrisV3-Interval database with respect to a segmentation made manually by a human expert. The proposed algorithm outperforms the baseline app...

A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Among most of the biometric methods, Iris recognition is regarded as the most reliable and accurate biometric identification system. The performance of iris recognition system highly depends on the accurate segmentation. For the Iris Segmentation there i...

Iris segmentation is an important step in iris recognition as inaccurate segmentation often leads to faulty recognition. We propose an unsupervised, intensity based iris segmentation algorithm in this paper. The algorithm is fully automatic and can work for varied levels of occlusion, illumination and different shapes of the iris. A near central point inside the pupil is first detected using in...

An iris based biometric recognition system provides identification of an individual based on a unique feature or characteristic possessed by that individual. Iris recognition is consider as the most reliable and accurate biometric identification system. In this paper we explore the performance of the iris based recognition system. We take iris image of ten different people and after segmentatio...

Iris segmentation is considered as the most difficult and fundamental step in an iris recognition system. While iris boundaries are largely approximated by two circles or ellipses, other methods define more accurately the iris resulting in better recognition results. In this paper we propose an iris segmentation method using Hough transform and active contour to detect a circular approximation ...

INTRODUCTION In the recent years, drastic improvements have been accomplished in the areas like iris recognition, automated iris segmentation, edge detection, boundary detection etc. Iris recognition is a biometric recognition technology that utilizes the pattern recognition techniques based on the high quality images of iris. An iris recognition system mainly uses infrared or else the visible ...

Iris recognition is regarded as the most stable and accurate biometric identification system. An iris recognition system basically consists of four stepssegmentation, normalization, encoding and matching. This paper proposes an efficient approach for iris segmentation. This segmentation approach uses a modified canny edge detection algorithm by considering gradient finding, nonmaximum suppressi...

Problem statement: Iris segmentation is one of the most important steps in iris recognition system and determines the accuracy of matching. Most segmentation methods in the literature assumed that the inner and outer boundaries of the iris were circular. Hence, they focus on determining model parameters that best fit these hypotheses. This is a source of error, since the iris boundaries were no...

A Biometric system is an automatic identification of an individual based on a unique feature or characteristic. Iris recognition has great advantage such as variability, stability and security. In this paper, use the two methods for iris segmentation -An automatic segmentation method and Window method. Window method is a novel approach which comprises two steps first finds pupils' center and th...

by Xiaomei Liu Biometric verification systems employing images of the iris are claimed to be extremely accurate, yielding no false accepts at any reasonable false reject rate. However, there are few if any large scale experimental evaluations on public iris datasets reported in the literature. We have collected an iris image dataset of over 25,000 iris images from over 300 persons (over 600 iri...