N. Shriram

Bio: N. Shriram is an academic researcher from VIT University. The author has contributed to research in topics: User interface & Iris recognition. The author has an hindex of 2, co-authored 2 publications receiving 16 citations.

A biometric security based electronic gadget control using hand gestures

Abstract: The control over electronic system using hand gestures is an innovative user interface that resolves the complications of using numerous remote controls for appliances. Founded on a unified set of hand gestures, this system interprets the user's hand gestures into pre-specified commands to control one or many devices simultaneously. However, of late, security has been of major concern among the people in using such a system, especially, at critical places like Home Entrances, Cashbox, etc. In order to minimize this issue, we have incorporated Biometric security through Iris recognition that will help in user authentication. Iris recognition, which is a relatively new biometric technology, has great advantages such as variability, stability and security. This proves to be very propitious for high security environments. This paper presents an elaboration of the methodologies employed including object recognition, artificial neural networks, and biometric security systems. All image processing was performed using NI Vision Assistant. In addition, NI LabVIEW was used to train and implement Neural Networks for Hand Gesture Classification. We have developed an automatic hand-gesture based control system that works after authentication (using Iris recognition) of the user.

A smart mobility solution for physically challenged

Abstract: This paper presents a hand gesture and a vision driven wheelchair system for physically handicapped people. The system is contrived to have a utilitarian design that caters to most of the disabilities rather than just one. In order to minimize system-human interaction, we have endeavored to present two distinct but closely related concepts viz. the hand gesture and vision based control system in conjunction for the wheelchair control. The wheelchair system is designed such that it provides for a natural and an intuitive user interface which can comprehend and react to in compliance with the users' instinctive volition which eases the mobility of the physically challenged people. All image processing was performed using NI Vision Assistant. NI LabVIEW was used to train and implement Neural Networks for Hand Gesture Classification and also to enable motion control. A prototype was developed on which all our experiments were successfully carried out. The system has been tested for users with varied hand shapes and proved to be extremely reliable.

A Survey of Iris Biometrics Research: 2008–2010

Abstract: A recent survey of iris biometric research from its inception through 2007, roughly 15 years of research, lists approximately 180 publications. This new survey is intended to update the previous one, and covers iris biometrics research over the period of roughly 2008–2010. Research in iris biometrics has expanded so much that, although covering only 3 years and intentionally being selective about coverage, this new survey lists a larger number of references than the inception-through-2007 survey.

Unimodal and Multimodal Biometric Sensing Systems: A Review

Abstract: Biometric systems are used for the verification and identification of individuals using their physiological or behavioral features. These features can be categorized into unimodal and multimodal systems, in which the former have several deficiencies that reduce the accuracy of the system, such as noisy data, inter-class similarity, intra-class variation, spoofing, and non-universality. However, multimodal biometric sensing and processing systems, which make use of the detection and processing of two or more behavioral or physiological traits, have proved to improve the success rate of identification and verification significantly. This paper provides a detailed survey of the various unimodal and multimodal biometric sensing types providing their strengths and weaknesses. It discusses the stages involved in the biometric system recognition process and further discusses multimodal systems in terms of their architecture, mode of operation, and algorithms used to develop the systems. It also touches on levels and methods of fusion involved in biometric systems and gives researchers in this area a better understanding of multimodal biometric sensing and processing systems and research trends in this area. It furthermore gives room for research on how to find solutions to issues on various unimodal biometric systems.

IR Sensor-Based Gesture Control Wheelchair for Stroke and SCI Patients

Abstract: This paper presents a novel and simple hand gesture recognition method to be used in rehabilitation of people who have mobility issues particularly stroke patients and patients with spinal cord injury (SCI). Keeping in mind the reach of such a system for a wider community of people with mobility issues, the proposed low-cost control device called gpaD—gesture pad provides an alternative solution to the joystick-based powered wheelchair control through hand gestures. In this method, IR sensors are used for identifying the simple gestures to control the powered wheelchair to move in any direction. In the proposed prototype system HanGes, a gesture pad that includes IR sensors, MCU and power management circuit is designed for gesture recognition and identification and a controller for driving motors is implemented. HanGes’s design, implementation, the response time calculations of the system, testing, performance evaluation with stroke and SCI patients are discussed in detail. With the average success rate of gesture recognition above 99.25% and response time as comparable with that of commercially available joystick controlled wheelchair, HanGes could be a possible alternative to the existing ones. With extensive experiments that demonstrate the accuracy of the system, the user experience, testing with patients, and the implementation cost indicate the superiority of our system.

Method for performing authentication using biometrics information and portable electronic device supporting the same

Abstract: A method for performing authentication in a portable electronic device is provided. The method includes identifying whether a peripheral electronic device is located within a certain distance from the portable electronic device, receiving biometrics information from the peripheral electronic device when the peripheral electronic device is located within the certain distance from the portable electronic device, identifying whether the biometrics information received from the peripheral electronic device is identical to biometrics information stored in the portable electronic device, and releasing security set to the portable electronic device when the biometrics information received from the peripheral electronic device is identical to the biometrics information stored in the portable electronic device.