Iris normalization is an important stage in any iris biometric, as it has a propensity to trim down the consequences of iris distortion. To indemnify the variation in size of the iris owing to the action of stretching or enlarging the pupil in iris acquisition process and camera to eyeball distance, two normalization schemes has been proposed in this work. In the first method, the iris region of interest is normalized by converting the iris into the variable size rectangular model in order to avoid the under samples near the limbus border. In the second method, the iris region of interest is normalized by converting the iris region into a fixed size rectangular model in order to avoid the dimensional discrepancies between the eye images. The performance of the proposed normalization methods is evaluated with orthogonal polynomials based iris recognition in terms of FAR, FRR, GAR, CRR and EER.

the tremendous growth of information resources in the World Wide Web (WWW) made the information retrieval process inefficient and irrelevant due to poor linking of data. One of challenging issues is to find the relevant information from web. Semantic web brings solution by meaningful information retrieval through unique semantic links. In this project, we propose a Self-Key Discovery algorithm based on Sematic Linking Network which allows systematically acquire keys to link RDF(Resource Description Framework) data resources with Semantic relationships among subject Ontologies. Data published on the WWW are usually generated automatically, thus may contain enormous information, duplicates or may be incomplete. RDF is used to represent web content which is the initial stage for semantic linking. SKD algorithm used for RDF data set only, Creation of RDF data is important step to implement semantic linking of data. Proposed Self Key Discovery technique is to performing semantic Linking on knowledge domain clusters using an Ontology Guided Data Linkage (OGDL) framework. This framework allows self-organization of contributing data resources through the discovery of semantic Keys, by performing Linking data of ontological domain knowledge relating to RDF resources. The framework thus automates the discovery of Key to link data across unrelated Resources, and different RDF data set for concept clustering and cluster mapping. In this project, demonstrate the feasibility of our Self Key Discovery algorithms through semantic links to set of RDF Resources, and run on real-world datasets.

The world is turning into a technological sphere. The technologies are evolving every second. With everything available in the Internet, people have started preferring to take their lectures and classes online. And so have the seminars turned into webinars, seminars over web. This system mainly concentrates on determining if a viewer attending the webinar is focused or not towards it. The main aim of this system is to recognize the eye gaze of a viewer over a live session with the help of some computer technologies and letting the presenter know if the viewer is focused on the session or not. By this, the presenter will know how well he/she is capable of keeping his viewers focused and he/she can work on his skills if the viewers are not focused. The access to the viewer's webcam is sufficient to achieve the goal.

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