Iris recognition is emerging as one of the important methods of biometrics-based identification system. It consists of five major steps iris acquisition, segmentation, normalization, feature extraction and matching. In this work, we used Wavelet transform function in place of Hough transform function. After extraction of feature of iris used feature optimizations technique for better selection ...

The biometric system is based on human's behavioral and physical characteristics. Among all of these, iris has unique structure, higher accuracy and it can remain stable over a person's life. Iris recognition is the method by which system recognize a person by their unique identical feature found in the eye. Iris recognition technology includes four subsections as, capturing of the ir...

–Iris recognition system has proven its capability in implementing reliable biometric security protocols in various high risk sectors like aviation, border patrol and defence. The banking and financial sector has to adoptthis system because of its robustness and the advantages it provides in cutting costs and making processes more streamlined. The technology started out as a novelty however due...

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 ...

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...

Abstract Recently, the Iris Recognition system has been considered an effective biometric model for recognizing humans. This paper introduces hybrid technique combining edge detection and segmentation, in addition to convolutional neural network (CNN) Hamming Distance (HD), extracting features classification. The proposed is applied different datasets, which are CASIA-Iris-Interval V4, IITD, MM...

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...

Iris recognition from surveillance-type imagery is an active research topic in biometrics. However, iris identification in unconstrained conditions raises many proplems related to localization and alignment, and typically leads to degraded recognition rates. While development has mainly focused on more robust preprocessing, this work highlights the possibility to account for distortions at matc...

Iris recognition as a biometric identification method is one of the most reliable human methods. It exploits distinctive pattern iris area. Typically, several steps are performed for recognition, namely, pre-processing, segmentation, normalization, extraction, coding and classification. In this article, we present novel algorithm that includes in addition to features extraction step feature sel...