A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities. (1st April 2020)

• Record Type: Journal Article
• Authors: Dargan, Shaveta; Kumar, Munish
• Is Part Of: Expert systems with applications. Volume 143(2020)
• Publication Date: 2020-04-01
• Subjects: Biometric -- Applications of biometric -- Biometric traits -- Feature extraction -- Classification; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2019.113114
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: This paper imparts a road map for the researchers of biometric recognition system. Highlights both Unimodal and multimodal biometric system. Covering diagrammatic view and major characteristics of all the biometric traits. Focus is given to the feature extraction methods, selection of the classifier. Datasets used and the accuracy achieved to explore the main ideas of the authors. Abstract: Biometrics is the branch of science that deals with the identification and verification of an individual based on the physiological and behavioral traits. These traits or identifiers are permanent, unique and can separate one individual from another. Biometric recognition systems integrate complex definitional, technological and operational selection under various contexts. The systems are not going to replace the authentication tools and technologies, but the combination of biometric approaches and authentication methods to help in improving the security aspects of the applications where user cooperation can be inferred. Biometric based recognition methods and tools have become popular for the development of many useful, challenging and widely accepted applications such as security issues, surveillance, forensic investigations, fraudulent technologies, identity access management and access control. These systems also help to identify an individual in group of industrial networks, home/office building and control system. For the successful implementation of the biometric systems, deep artificial neural networks are in great demand. These systems can be built up either on the single modality or multiple modalities. This article explicates the comprehensive and deep survey that compactly and systematically summarizes the literature work done on unimodal and multimodal biometric systems and analyzes the feature extraction techniques, classifiers, datasets, results, efficiency and reliability of the system with high and multi-dimensional perspectives. This article also justifies in detail the classical methods, influential methods and taxonomy based on the biometric attributes. The goal is to aware the researchers of this area regarding various dimensions for the development of biometric systems to enhance the security aspects. The article begins with the fundamentals, types, need of system, challenges, uncertainties, motivations and then to the survey work. The tabular representation prepares for each biometric trait shows the author, year, major findings and results achieved with the synthesis analysis and the evaluation. The article finally ends up with the 3D biometric, a future perspective and concluding remarks.