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

Springer Science and Business Media LLC - Tập 15 - Trang 1-18 - 2020
Syed Farooq Ali1, Muhammad Aamir Khan2, Ahmed Sohail Aslam3
1Department of Software Engineering, University of Management and Technology, Lahore, Pakistan
2Department of Informatics and Systems, University of Management and Technology, Lahore, Pakistan
3Department of Computer Science, University of Management and Technology, Lahore, Pakistan

Tóm tắt

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.

Tài liệu tham khảo

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