Iris segmentation is an important step in the process of iris recognition. images collected under non-cooperative conditions always contain various noise, which a challenge for segmentation. Most U-Net-based methods have made great achievements However, this architecture lacks focusing on target structures varying shapes, and robustness segmenting objects with significant shape variations. In p...

Iris recognition, the ability to recognize and distinguish individuals by their pattern, is the most reliable biometric in terms of recognition and identification performance. However, performance of these systems is affected by the heterogeneous images (regarding focus, contrast, or brightness) and with several noise factors (iris obstruction and reflection) when the cooperation is not expecta...

This paper introduces an efficient approach to protect the ownership by hiding the iris data into a digital image for authentication purposes. The idea is to secretly embed an iris code data into the content of the image, which identifies the owner. Algorithms based on Biologically inspired Spiking Neural Networks, called Pulse Coupled Neural Network (PCNN) are first applied to increase the con...

In eye authentication process, the pupil detection is most crucial step to recognize the eye. In eye, iris and sclera are used as the previous inputs using to recognize the eye with different mechanisms like segmentation combining with different versions. The inner edge in the eye is not a normal circle, which may create problem in accurate recognition. In segmentation process, if the image is ...

Abstract— The human iris recognition system is an attractive technology for identity authentication. This technology benefits from random variations in the features of the iris. Usually, an iris recognition system has 4 modules: segmentation, normalization, feature extraction and iris templates matching. This work is mainly focused on iris texture analysis and templates matching which are 2 ess...

Multispectral Iris Recognition Analysis: Techniques and Evaluation by Christopher K. Boyce Master of Science in Electrical Engineering West Virginia University Lawrence Hornak, Ph.D., Chair Arun Ross, Ph.D. (Co-chair) This thesis explores the benefits of using multispectral iris information acquired using a narrow-band multispectral imaging system. Commercial iris recognition systems typically ...

Iris recognition has been demonstrated to be an efficient technology for personal identification. In this work, methods to perform iris encoding using bi-orthogonal wavelets and directional bi-orthogonal filters are proposed and compared. All the iris images are enhanced using the wavelet domain in-band de-noising method. This method is shown to improve the iris segmentation results. A framewor...

Accurate iris detection is a crucial part of an iris recognition system. One of the main issues in iris segmentation is coping with occlusion that happens due to eyelids and eyelashes. In the literature, some various methods have been suggested to solve the occlusion problem. In this paper, two different segmentations of iris are presented. In the first algorithm, a circle is located around the...

A biometric system is used for recognition of individual based on their physical or personal characteristics. Biometric system includes face recognition, fingerprint recognition, voice recognition , the Iris recognition etc. various study has shown that iris recognition is the most efficient biometrics. hence the work presented here involved designing a user friendly GUI based efficient and opt...

People upload daily a huge number of portrait face pictures on websites and social media, which can be processed using biometric systems based the characteristics to perform an automatic recognition individuals. However, performance approaches limited by negative factors as aging, occlusions, rotations, uncontrolled expressions. Nevertheless, constantly increasing quality resolution uploaded me...