Palmprint Authentication Techniques: A Comparative Study

Abstract

Biometrics authentication has various advantages over traditional authentication systems, including greater security, convenience, and resistance against fraud and theft. However, issues regarding privacy, accuracy, and possible vulnerabilities like spoofing or hacking must still be addressed throughout development and deployment. In recent years, palm print identification has evolved as a key area of study and application within the larger field of biometrics, owing to its high accuracy, non-invasiveness, and resilience against fraudulent efforts. This paper discusses the challenges associated with palmprint authentication, including image quality, illumination variations, and spoof attacks, and provides a full analysis of palmprint authentication techniques, including both old approaches and current improvements. Each phase of palmprint authentication, such as picture capturing, preprocessing, feature extraction, and matching is described in detail. Furthermore, several palmprint identification techniques, including minutiae-based methods, texture-based methods, and deep learning-based approaches are investigated highlighting the strengths and limitations of existing palmprint authentication systems and identifying potential areas for future research and improvement. Overall, this review provides valuable insights into state-of-the-art palmprint authentication techniques and their applications in real-world scenarios. It is a reference for researchers, practitioners, and policymakers interested in understanding and advancing palmprint authentication technology.