Perfect Fingerprint Orientation Fields by Locally Adaptive Global Models
University of Göttingen（哥廷根大学）；Institute for Mathematical Stochastics（数学随机研究所）；Felix-Bernstein-Institute for Mathematical Statistics in the Biosciences（生物科学数学统计费利克斯-伯恩斯坦研究所）
Carsten Gottschlich, Benjamin Tams, Stephan Huckemann
发表信息：
IET Biometrics, vol. 6, no.3, pp. 183-190, May 2017
Fingerprint recognition is widely used for verification and identification in many commercial, governmental and forensic applications. The orientation field (OF) plays an important role at various processing stages in fingerprint recognition systems. OFs are used for image enhancement, fingerprint alignment, for fingerprint liveness detection, fingerprint alteration detection and fingerprint matching. In this paper, a novel approach is presented to globally model an OF combined with locally adaptive methods. We show that this model adapts perfectly to the 'true OF' in the limit. This perfect OF is described by a small number of parameters with straightforward geometric interpretation. Applications are manifold: Quick expert marking of very poor quality (for instance latent) OFs, high fidelity low parameter OF compression and a direct road to ground truth OFs markings for large databases, say. In this contribution we describe an algorithm to perfectly estimate OF parameters automatically or semi-automatically, depending on image quality, and we establish the main underlying claim of high fidelity low parameter OF compression.
DWT Based Fingerprint Recognition using Non Minutiae Features
Cambridge Institute of Technology（剑桥理工学院）；University Visvesvaraya College of Engineering（维斯瓦瓦拉亚工程大学学院）；Bangalore University（班加罗尔大学）；Seemanta Engineering College（西曼塔工程学院）；F.M. University（F.M.大学）
A B-Spline Function Based 3D Point Cloud Unwrapping Scheme for 3D Fingerprint Recognition and Identification
School of Systems and Computing, UNSW Canberra（UNSW Canberra 系统与计算学院）；Information Systems, University of Canberra（堪培拉大学信息系统系）；School of Information and Communication Technology, Griffith University（格里菲斯大学信息与通信技术学院）；School of Engineering & Technology, UNSW Canberra（UNSW Canberra 工程与技术学院）
Singular points detection with semantic segmentation networks
Molecular and Neuroimaging Engineering Research Center of MOE, School of Life Science and Technology, Xidian University（教育部分子与神经影像工程研究中心，西安电子科技大学生命科学技术学院）
G-MSGINet: A Grouped Multi-Scale Graph-Involution Network for Contactless Fingerprint Recognition
Department of Computer Science and Engineering（计算机科学与工程系）；Advanced Technology Development Centre（先进技术发展中心）；School of Quality and Reliability（质量与可靠性学院）；Indian Institute of Technology Kharagpur（印度理工学院Khargpur分校）
Latent fingerprint enhancement for accurate minutiae detection
TCC Research and Development Labs, Technology Control Company（TCC研发实验室，技术控制公司）；University of New South Wales（新南威尔士大学）；Abasyn University Islamabad（阿巴辛伊斯兰堡大学）；Computer and Information Sciences College, Jouf University（焦夫大学计算机与信息科学学院）
Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection
Beihang University（北京航空航天大学）；Beijing Advanced Innovation Center for Big Data-Based Precision Medicine（北京大数据精准医疗高精尖创新中心）；Wuhan University（武汉大学）；JD Explore Academy（京东探索研究院）；The University of Sydney（悉尼大学）
A bisector line field approach to interpolation of orientation fields
Laboratoire d’Informatique et des Systèmes, Université de Toulon, Aix Marseille Univ, CNRS UMR 7020, LIS（土伦大学计算机与系统实验室，艾克斯-马赛大学，法国国家科学研究中心 UMR 7020，LIS）；Department of Mathematics, Lehigh University（里海大学数学系）
A robustness measure for singular point and index estimation in discretized orientation and vector fields
Technische Universität Dresden（德累斯顿工业大学）；Max Planck Institute of Molecular Cell Biology and Genetics（马克斯·普朗克分子细胞生物学与遗传学研究所）；Center for Systems Biology Dresden（德累斯顿系统生物学中心）
