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Fingerprint matching, spoof and liveness detection: classification and literature review

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Abstract

Fingerprint matching, spoof mitigation and liveness detection are the trendiest biometric techniques, mostly because of their stability through life, uniqueness and their least risk of invasion. In recent decade, several techniques are presented to address these challenges over well-known data-sets. This study provides a comprehensive review on the fingerprint algorithms and techniques which have been published in the last few decades. It divides the research on fingerprint into nine different approaches including feature based, fuzzy logic, holistic, image enhancement, latent, conventional machine learning, deep learning, template matching and miscellaneous techniques. Among these, deep learning approach has outperformed other approaches and gained significant attention for future research. By reviewing fingerprint literature, it is historically divided into four eras based on 106 referred papers and their cumulative citations.

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Acknowledgements

We are very grateful to Dr. Umar Suleman for his support and guidance. We also like to extend our gratitude to Sundas Ayaz, Afnan Muneer, Hafiza Anam Atique and Hafsa Mateen for their assistance. We are grateful to all the anonymous reviewers for their useful comments. This work was supported by the National ICT R&D (NICTRDF/NGIRI/2012-13/Corsp/3), and University of Management & Technology, Pakistan.

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Authors and Affiliations

  1. Department of Software Engineering, University of Management and Technology, Lahore, 54770, Pakistan

    Syed Farooq Ali

  2. Department of Informatics and Systems, University of Management and Technology, Lahore, 54770, Pakistan

    Muhammad Aamir Khan

  3. Department of Computer Science, University of Management and Technology, Lahore, 54770, Pakistan

    Ahmed Sohail Aslam

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  1. Syed Farooq Ali
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  2. Muhammad Aamir Khan
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Correspondence to Syed Farooq Ali.

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Syed Farooq Ali received his PhD (CS) from UMT, Pakistan. He did his PhD course work, PhD Comprehensive exam and MS (CS) from Ohio State University, USA. He also completed his MS (CS) from LUMS, Pakistan with Deans Honor List. During his stay in MS, he was on LUMS fellowship. He is currently working as an Assistant Professor, UMT. His research interest includes computer vision, digital image processing and medical imaging. He is a reviewer for various IEEE conferences and journals.

Muhammad Aamir Khan is currently working as an assistant professor in the School of Systems and Technology (SST) at the University of Management and Technology Lahore, Pakistan. He holds a PhD in electronic engineering from the University of Twente, the Netherlands and three master degrees in System-on-Chip Design, Systems Engineering (Control Engineering) and Physics (Electronics) from the Royal Institute of Technology (KTH), Sweden, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad and University of the Punjab (PU), Lahore respectively. He has several years of experience in research and development including experience of working in reputed international and local organizations at senior positions. His research interest includes Electronic Design for DSP, Control/Communication, and Image Processing Applications.

Ahmed Sohail Aslam received his BSc in Electrical Engineering from University of Engineering & Technology, Pakistan in 1998 and MSc in Computer Science from University of South Florida, USA in 2006. He is currently working as an Assistant Professor in School of Systems and Technology, University of Management & Technology, Pakistan. His research interests include biometrics, digital image processing, and computer networks.

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Ali, S.F., Khan, M.A. & Aslam, A.S. Fingerprint matching, spoof and liveness detection: classification and literature review. Front. Comput. Sci. 15, 151310 (2021). https://doi.org/10.1007/s11704-020-9236-4

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