Research Area:  Machine Learning

Abstract:

Biometric deals with the verification and identification of a person based on behavioural and physiological traits. This article presents recent advances in physiological-based biometric multimodalities, where we focused on finger vein, palm vein, fingerprint, face, lips, iris, and retina-based processing methods. The authors also evaluated the architecture, operational mode, and performance metrics of biometric technology. In this article, the authors summarize and study various traditional and deep learning-based physiological-based biometric modalities. An extensive review of biometric steps of multiple modalities by using different levels such as preprocessing, feature extraction, and classification, are presented in detail. Challenges and future trends of existing conventional and deep learning approaches are explained in detail to help the researcher. Moreover, traditional and deep learning methods of various physiological-based biometric systems are roughly analyzed to evaluate them. The comparison result and discussion section of this article indicate that there is still a need to develop a robust physiological-based method to advance and improve the performance of the biometric system.

Keywords:  

Author(s) Name:  Kashif Shaheed, Aihua Mao, Imran Qureshi, Munish Kumar, Qaisar Abbas, Inam Ullah & Xingming Zhang

Publisher name:  Springer

DOI:  10.1007/s11831-021-09560-3

Volume Information:  volume 28, pages:4917–4960 (2021)

Paper Link:   https://link.springer.com/article/10.1007/s11831-021-09560-3