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.

指纹匹配，缓解欺骗和活动检测是最流行的生物识别技术，主要是因为它们在生命中具有稳定性，独特性以及最小的入侵风险。在最近的十年中，提出了几种技术来应对众所周知的数据集的这些挑战。这项研究对最近几十年来发表的指纹算法和技术进行了全面回顾。它将指纹研究分为九种不同的方法，包括基于特征，模糊逻辑，整体，图像增强，潜在，常规机器学习，深度学习，模板匹配和其他技术。其中，深度学习方法已超越其他方法，并受到了未来研究的极大关注。通过回顾指纹文献，