Biometric Recognition: Latest Advances and Prospects, 2nd Edition

Dear Colleagues,

Biometric recognition empowers a machine to automatically detect, capture, process, analyze, and recognize digital physiological or behavioral signals with advanced intelligence. Biometrics, such as the face, iris, and fingerprint recognition, have become digital identity proof for people to enter the “Internet of Everything”. Biometric recognition 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. This Special Issue aims to provide a platform for researchers from various fields to exchange recent advances in biometric recognition and present their novel research and the latest results dedicated to biometric recognition. It also strives to spur research in emerging directions.

Any area of biometrics is within the scope of this Special Issue, and possible areas of interest include (but are not limited to):

• Latest advances in biometric sensor design and data collection;
• Approaches for trustworthy biometrics (e.g., related topics in bias and fairness, privacy and security, robustness, explainability, transparency, etc.);
• Biometric recognition aided with generative models;
• Developments of multimodal or multispectral biometrics;
• Human identification at a distance in less cooperative environments;
• Open-set liveness detection, anti-spoofing in the wild;
• Efficient biometric algorithms for light architectures (e.g., match-on-card/board, mobile platforms, etc.);
• Biometric applications in Metaverse.

Submissions must not be published or presented in part or entirety or considered for publication elsewhere. Conference papers may be submitted only if they are substantially extended (more than 50%) and must be referenced. All submitted papers will be peer-reviewed and accepted based on quality, originality, novelty, and relevance to the theme of the Special Issue. 

Dr. Yunlong Wang
Prof. Dr. Zhaofeng He
Dr. Caiyong Wang
Dr. Jianze Wei
Dr. Min Ren
Guest Editors

Manuscript Submission Information

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