Enhanced iris recognition for security superpixel segmentation and ensemble classification

Abstract

Owing to the advancement of technology, the utilization of remote data storage and online transactions increases in an exponential mode. This trend of remote data storage and online transactions stimulates the hackers or attackers to gain illegitimate access to the data. This scenario results in a serious issue and several security enforcement algorithms are required to handle this issue. In order to provide security, numerous cryptographic algorithms are proposed in the existing literature. However, these algorithms are difficult to understand and involve computational complexity. At this juncture, the biometric based security algorithms grabbed the attention of the researchers, which do not involve any complex manipulations. The biometric based security applications simply prompt the users to be present for gaining access to the application. Based on the nature and the need of the application, the biometrics is chosen by the developers. Basically, a biometric based security application is based on four significant phases, which are biometric image pre-processing, segmentation, feature extraction and classification. The entire system is based on two phases, which are enrolment and verification. In the enrolment phase, the specific biometric of the user is captured, preprocessed, segmented and the features are extracted from the region of interest. The computed features are stored in the database and the classifier is trained up with the so formed feature vector. newline