Overview of biometrics research

Abstract

Biometrics, such as face, iris, and fingerprint recognition, have become digital identity proof for people to enter the “Internet of Everything” . For example, one may be asked to present the biometric identifier for unlocking mobile, passing access control at airports, rail stations, and paying at supermarkets or restaurants. Biometric recognition empowers a machine to automatically detect, capture, process, analyze, and recognize digital physiological or behavioral signals with advanced intelligence. Thus, biometrics requires interdisciplinary research of science and technology involving optical engineering, mechanical engineering, electronic engineering, machine learning, pattern recognition, computer vision, digital image processing, signal analysis, cognitive science, neuroscience, human-computer interaction, and information security. Biometrics is a typical and complex pattern recognition problem, which is a frontier research direction of artificial intelligence. In addition, biometric identification is a key development area of Chinese strategies, such as the Development Plan on the New Generation of Artificial Intelligence and the “Internet Plus” Action Plan. The development of biometric identification involves public interest, privacy, ethics, and law issues; thus, it has also attracted widespread attention from the society. This article systematically reviews the development status, emerging directions, existing problems, and feasible ideas of biometrics and comprehensively summarizes the research progress of face, iris, fingerprint, palm print, finger / palm vein, voiceprint, gait recognition, person reidentification, and multimodal biometric fusion. The overview of face recognition includes face detection, facial landmark localization, 2D face feature extraction and recognition, 3D face feature extraction and recognition, facial liveness detection, and face video based biological signal measurement. The overview of iris recognition includes iris image acquisition, iris segmentation and localization, iris liveness detection, iris image quality assessment, iris feature extraction, heterogeneous iris recognition, fusion of iris and other modalities, security problems of iris biometrics, and future trends of iris recognition. The overview of fingerprint recognition includes latent fingerprint recognition, fingerprint liveness detection, distorted fingerprint recognition, 3D fingerprint capturing, and challenges and trends of fingerprint biometrics. The overview of palm print recognition mainly introduces databases, feature models, matching strategies, and open problems of palm print biometrics. The overview of vein biometrics introduces main datasets and algorithms for finger vein, dorsal hand vein, and palm vein, and then points out the remaining unsolved problems and development trend of vein recognition. The overview of gait recognition introduces model-based and model-free methods for gait feature extraction and matching. The overview of person reidentification introduces research progress of new methods under supervised, unsupervised and weakly supervised conditions, gait database virtualization, generative gait models, and new problems, such as clothes changing, black clothes, and partial occlusions. The overview of voiceprint recognition introduces the history of speaker recognition, robustness of voiceprint, spoofing attacks, and antispoofing methods. The overview of multibiometrics introduces image-level, feature-level, score-level, and decision-level information fusion methods and deep learning based fusion approaches. Taking face as the exemplar biometric modality, new research directions that have received great attentions in the field of biometric recognition in recent years, i. e. , adversarial attack and defense as well as Deepfake and anti-Deepfake, are also introduced. Finally, we analyze and summarize the three major challenges in the field of biometric recognition——— “ the blind spot of biometric sensors”, “ the decision errors of biometric algorithms” and “the red zone of biometric security” . Therefore, the sensing, cognition, and security mechanisms of biometrics are necessary to achieve a fundamental breakthrough in the academic research and technologies applications of biometrics in complex scenarios to address the shortcomings of the existing biometric technologies and to move towards the overall goal of developing a new generation of “ perceptible, “ robust”, and “ trustworthy” biometric identification technology.