Sasikumar Gurumurthy

Work place: School of Computer Science and Engineering, VIT University, Vellore, Tamil Nadu, India



Research Interests: Computational Science and Engineering, Artificial Intelligence, Swarm Intelligence, Data Structures and Algorithms


SASIKUMAR Gurumurthy is a Assistant professor (Senior) in the school of computing sciences and engineering, VIT University, at Vellore, Tamil Nadu, India, has published more than 38 technical papers in international journals/ proceedings of international conferences. He is having more than 6 years of teaching experience. He is a member of international professional associations like CSI, IAENG and AIRCC and is a reviewer of AIRCC international journals. Also, he is in the editorial board of AIRCC. His current research directions include detecting technique and signal processing, intelligence computation and soft computing.

Author Articles
Design and Implementation of Face Recognition System in Matlab Using the Features of Lips

By Sasikumar Gurumurthy B.K. Tripathy

DOI:, Pub. Date: 8 Jul. 2012

Human Face Recognition systems are an identification procedure in which a person is verified based on human traits. This paper describes a fast face detection algorithm with accurate result. Lip Tracking is one of the biometric systems based on which a genuine system can be developed. Since the uttering characteristics of an individual are unique and difficult to imitate, lip tracking holds an advantage of making the system secure. We use pre- recorded visual utterance of speakers has been generated and stored in the database for future verification. The entire project occurs in four different stages in which the first stage includes obtaining face region from the original image, the second stage includes mouth region extraction by background subtraction, the third stage includes key points extraction by considering the lip centroid as origin of co-ordinates and the fourth stage includes storing the obtained feature vector in the database. The user who wants to be identified by the system provides the new live information, which is then compared with the existing template in the database. The feedback provided by the system will be ‘a match or a miss-match’. This project will increase the accuracy level of biometric systems.

[...] Read more.
Other Articles