CSE/MNIT GIAN Course on Multimodal and Advanced Biometrics Authentication 2017.
If you have already registered please download the Joining instructions (PDF, 180KB) and Course Brochure
Automated human recognition in real environments is one of the most critical and challenging tasks to meet the growing demand for stringent security. Biometrics authentication of individuals establishes identity of an unknown individual using their physiological or behavioural features. Unlike password or PIN, biometrics cannot be forgotten or lost and requires physical presence of the person to be authenticated. Thus personal authentication systems using biometrics are more reliable, convenient and efficient than the traditional identification methods. Biometrics is increasingly adapted and researched in the computer science community as the most reliable means of identification and access control. It is also used to identify individuals in groups that are under surveillance. A biometric system is based on the measurement of an individual's unique physiological and behavioural characteristics. The most common measurements such as fingerprints, hand geometry, palmprint, facial features and iris patterns are physiological features for biometrics. Some of the more novel measurements, such as body odor, finger knuckle, brain wave patterns, DNA, ear shape, sweat pores, and vein patterns also fall into the category of physiological measurements for biometrics.
The course is residential, spanning 10 days, and consists of lectures and hands-on experiences relating to diverse topics on Biometrics authentication. It is intended that the course will complement and extend the materials in existing technical courses that many students will encounter in their first year of postgraduate training. It will also provide an opportunity to broaden awareness of knowledge and techniques in Biometrics, Security, Pattern Recognition, Vision, and Image Computing, and to develop appropriate research skills. (View: Programme).
The course is open to the teachers and research students from Computer, Electrical and Electronics Engineering Departments of Govt/ Govt. aided/ self-financed Engineering colleges, Engineers from Industries, Public sector undertakings and utilities. This intensive workshop is aimed at research in Machine vision, Pattern Recognition and Digital Image Computing, including topics such as Image Processing and Computer Vision. It is intended that the course will complement and extend the material in existing technical courses that many students will encounter in their first year of postgraduate training. It will provide an opportunity to broaden awareness of knowledge and techniques in Biometrics, Security, Pattern Recognition, Vision, and Image Computing, and to develop appropriate research skills.
It is organised under the auspices of Malaviya National Institute of Technology Jaipur, hosted by the Department of Computer Science and Engineering, Pattern Recognition research group (DCSEPR).