**Iris Recognition System using SVM Classifier**

Problem Definition

PROBLEM DESCRIPTION: One of the critical challenges faced by organizations and individuals is ensuring secure access to sensitive information and physical spaces. Traditional methods of authentication such as passwords and tokens are vulnerable to hacking and theft, leading to an increase in security breaches. As a result, there is a need for more advanced and reliable authentication methods, such as biometric recognition. Iris recognition is considered one of the most secure biometric authentication methods due to the unique characteristics of the iris. However, the implementation of iris recognition systems requires efficient and accurate image processing techniques to compare the captured iris image with the stored database images.

The use of Support Vector Machine (SVM) based Iris Image Recognition System can address this issue by providing a reliable and accurate method for comparing iris images. By implementing a SVM classifier, the system can accurately match the current subject's iris with the stored database images, ensuring a low false acceptance and rejection rate. This system can be used in various security applications such as information security, physical access security, ATMs, and airport security to enhance overall system security and reduce the risk of unauthorized access.

Proposed Work

The proposed work entitled "Support Vector Machine(SVM) based Iris Image Recognition System" focuses on enhancing security in systems by implementing iris recognition biometric technology. The project utilizes a support vector machine classifier to compare captured iris images with stored versions, providing a highly accurate authentication method with low false acceptance and rejection rates. This technology has applications in information security, physical access security, ATMs, and airport security. The project modules include Relay Driver (Auto Electro Switching) using ULN-20, Relay Based AC Motor Driver, Metal Detector Sensor, Basic Matlab, and MATLAB GUI. This research falls under the categories of BioMedical Based Projects, Image Processing & Computer Vision, M.

Tech | PhD Thesis Research Work, and MATLAB Based Projects, specifically focusing on Image Processing Based Diagnose Projects, Image Classification, and Iris Recognition. The software used for this project is MATLAB. By implementing this iris recognition system, the project aims to contribute to the advancement of secure authentication methods in various security applications.

Application Area for Industry

The "Support Vector Machine (SVM) based Iris Image Recognition System" project can be applied across various industrial sectors where secure access to sensitive information and physical spaces is a critical concern. Industries such as finance, healthcare, government, and transportation can greatly benefit from the enhanced security provided by biometric authentication technologies like iris recognition. By implementing a SVM classifier for iris image comparison, the system ensures high accuracy in matching current subjects with stored database images, reducing the risk of unauthorized access. This solution addresses the challenge of traditional authentication methods being vulnerable to hacking and theft, providing a more reliable and advanced security measure. The project's proposed solutions can be implemented in security applications such as information security, physical access security, ATMs, and airport security, offering industries a more secure environment and peace of mind when it comes to sensitive data and restricted access areas.

Application Area for Academics

The proposed project "Support Vector Machine(SVM) based Iris Image Recognition System" offers MTech and PhD students a valuable platform for conducting innovative research in the field of biometric authentication and security systems. With the increasing demand for advanced security measures to combat hacking and unauthorized access, the utilization of iris recognition technology can significantly enhance security in various applications such as information security, physical access security, ATMs, and airport security. By utilizing SVM classifier, the system ensures a highly accurate comparison of captured iris images with stored database images, thereby reducing the risk of false acceptance and rejection rates. The project modules encompass Relay Driver (Auto Electro Switching) using ULN-20, Relay Based AC Motor Driver, Metal Detector Sensor, Basic Matlab, and MATLAB GUI, emphasizing the practical implementation of the system in real-world scenarios. This project is particularly relevant for researchers in the BioMedical field, Image Processing & Computer Vision, and those pursuing research in MATLAB-based projects focusing on Image Processing Based Diagnose Projects, Image Classification, and Iris Recognition.

The utilization of MATLAB software for this project provides students with a versatile tool for data analysis, simulations, and innovative research methods in the domain of iris recognition biometrics. With its potential applications in enhancing security systems, the project offers students a rich source of code, literature, and methodologies that can be applied in their dissertations, theses, and research papers. Furthermore, the future scope of this project suggests possibilities for further advancements in secure authentication methods and the integration of iris recognition technology in various security applications.

Keywords

Biometric Authentication, Iris Recognition, Support Vector Machine, SVM Classifier, Image Processing, Security System, Secure Access, Information Security, Physical Access Security, ATM Security, Airport Security, Biometric Technology, Relay Driver, AC Motor Driver, Metal Detector Sensor, MATLAB GUI, BioMedical Projects, Computer Vision, M.Tech Thesis, PhD Research Work, Image Classification, Image Acquisition, Medical Diagnosis, Cancer Detection, Skin Problem Detection, Neural Network, Neurofuzzy, Classifier, Opti Disk, Linpack.