Enhancing Computer Vision Enabled Biometric Applications
Chinu Singla · 2024
This chapter explores the significant advancements in computer vision techniques for biometric applications and highlights the challenges faced in this domain along with potential solutions. Biometrics, which involves the identification and verification of individuals based on unique physical or behavioural characteristics, has gained great importance in various sectors, including security, access control, surveillance and personal authentication. Computer vision plays a crucial role in extracting and analysing biometric features from images or video data by enabling accurate identification and verification. However, several challenges such as variations in lighting conditions, pose and ageing effects pose significant obstacles to achieving reliable biometric systems. This chapter aims to provide an overview of the latest computer vision approaches used in biometric applications, including face recognition, fingerprint identification and iris recognition. It also discusses the challenges encountered in each of these areas and presents potential solutions, including deep learning techniques, data augmentation, feature extraction and fusion methods. By addressing these challenges and using innovative solutions, the effectiveness and reliability of biometric systems can be significantly enhanced resulting in secure and efficient applications.