RESEARCH OF PERSONAL IDENTIFICATION METHODS BY BIOMETRIC CHARACTERS

Abstract

The article is devoted to the analysis of modern biometric identification technologies and their use in various areas, such as security, government and commercial organizations. The main goal of the research is a comprehensive study of various biometric methods, such as face recognition, fingerprints, iris, voice and other features, with further development of recommendations for their implementation. The paper provides an overview of modern biometric identification methods that are actively used in various industries. Algorithms for face recognition based on deep neural networks are considered, which provide high accuracy even in difficult conditions. In addition, fingerprint recognition methods are analyzed, which are widely used due to their availability and reliability. Iris and voice recognition have also been recognized for high accuracy and speed in specific conditions. The article examines assessments of the accuracy and effectiveness of biometric methods in various conditions of use. Important aspects are the quality of the input data (image or signal), lighting conditions, the presence of noise and other external factors that can affect the recognition results. The speed and computing costs of each method were also studied, which made it possible to compare their effectiveness. Part of the research focuses on applying machine learning and artificial intelligence techniques to improve the accuracy and speed of biometric recognition. The use of deep neural networks allows for significant improvements in accuracy, especially when working with large data sets. Machine learning also helps to adapt systems to different usage conditions, increasing their reliability and resistance to distortions. The article proposes a generalized mathematical model for choosing the optimal method of biometric identification. The model is based on a multi-criteria approach, which includes the assessment of such parameters as accuracy, speed, reliability, resistance to external influences and computational costs. This allows you to choose the most optimal method for specific applications. Based on the analysis, recommendations were formulated for the introduction of biometric systems. Recommendations for security, government structures and commercial organizations have been developed, including the use of facial recognition, fingerprints and combined biometric systems to improve efficiency and security. This research contributes to the development of biometric identification technologies, providing a basis for further implementation of effective solutions in various industries.