Real Time Face Recognition using EBGM for Enhanced Security

Problem Definition

PROBLEM DESCRIPTION: The problem of security in biometric systems, specifically face recognition systems, is a growing concern in today's world. Traditional methods of feature extraction and identification may not be robust enough to prevent unauthorized access or identity theft. There is a need for a more advanced, real-time solution that can accurately extract features from live video streams and improve the overall security of face recognition systems. The current project aims to address this issue by utilizing the EBGM feature extraction methodology to enhance the accuracy and reliability of face recognition systems.

Proposed Work

The proposed project titled "Live Face classification using EBGM feature extraction methodology" focuses on enhancing security through biometric recognition using face recognition technology. The project aims to create a real-time application for feature extraction from live video using the Elastic Bunch Graph Matching (EBGM) technique in MATLAB software. EBGM is an algorithm that recognizes objects in an image based on graphical representation, making it ideal for gesture and facial feature detection. This M.tech project can be applied to medical analysis and improve the authentication and reliability of face recognition systems.

By utilizing modules such as Regulated Power Supply and IR Transceiver as a Proximity Sensor, along with MATLAB GUI, the project showcases a design and implementation to enhance security in face recognition systems. This project falls under the categories of Biometric Based Projects, Image Processing & Computer Vision, and Security, Authentication & Identification Systems with subcategories focusing on face recognition systems, feature extraction, and real-time application control systems.

Application Area for Industry

This project on "Live Face classification using EBGM feature extraction methodology" can be utilized in a variety of industrial sectors such as healthcare, finance, government, and technology. In the healthcare sector, this project can be used to enhance the security and reliability of patient identification systems, ensuring accurate medical records and treatment procedures. In the finance sector, the project can help in improving the authentication process for secure transactions and access control. Government agencies can benefit from this project by enhancing the security of biometric identification systems for border control, identity verification, and criminal investigations. Technology companies can integrate this solution into their security systems to protect sensitive data and prevent unauthorized access.

The proposed solutions in this project address the specific challenges that industries face in terms of security, authentication, and reliability of face recognition systems. By utilizing the EBGM feature extraction methodology, the project enhances the accuracy and robustness of biometric recognition systems, making them more resistant to unauthorized access and identity theft. The real-time application of feature extraction from live video streams ensures quick and accurate identification of individuals, improving efficiency and security in various industrial domains. Implementing this project's solutions can result in benefits such as enhanced data protection, streamlined authentication processes, reduced risk of security breaches, and improved overall security measures in different industrial sectors.

Application Area for Academics

The proposed project on "Live Face classification using EBGM feature extraction methodology" presents a significant opportunity for MTech and PHD students to engage in innovative research within the domain of biometric systems and face recognition technology. This project addresses the pressing issue of security in biometric systems by focusing on real-time feature extraction using the EBGM technique in MATLAB software. This offers a unique platform for students to explore advanced methods of feature extraction and identification to enhance the accuracy and reliability of face recognition systems. MTech and PHD students can utilize this project for their research by conducting simulations, data analysis, and algorithm development for dissertation, thesis, or research papers. By incorporating modules such as Regulated Power Supply and IR Transceiver as a Proximity Sensor, along with MATLAB GUI, students can experiment with different design and implementation approaches for improving security in face recognition systems.

Moreover, this project covers various technology areas such as Biometric Based Projects, Image Processing & Computer Vision, and Security, Authentication & Identification Systems, providing a diverse range of applications for researchers to explore. Overall, this project offers a valuable opportunity for MTech students and PHD scholars to delve into cutting-edge research methods and contribute to advancements in face recognition technology. In the future, this project could be expanded to incorporate additional features such as multi-modal biometric systems or deep learning algorithms for further enhancing security in biometric systems.

Keywords

Biometric, Face recognition, Facial recognition, Feature extraction, EBGM, MATLAB, Computer vision, Image processing, Security, Authentication, Identification, Real-time application, Face expression recognition, Gesture recognition, Image recognition, Biometrics, Neural network, ANN, PCA, Eigen, Histogram, Classification, Matching, Access control systems, Image acquisition, Medical analysis, Regulated power supply, IR Transceiver, Proximity sensor, GUI, Design and implementation, Biometric based projects, Latest projects, New projects