MICHE Competitions: A Realistic Experience with Uncontrolled Eye Region Acquisition
暂无分享,去创建一个
[1] Luís A. Alexandre,et al. Toward Covert Iris Biometric Recognition: Experimental Results From the NICE Contests , 2012, IEEE Transactions on Information Forensics and Security.
[2] Kang Ryoung Park,et al. IrisDenseNet: Robust Iris Segmentation Using Densely Connected Fully Convolutional Networks in the Images by Visible Light and Near-Infrared Light Camera Sensors , 2018, Sensors.
[3] Dexin Zhang,et al. Personal Identification Based on Iris Texture Analysis , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[4] Shahrel Azmin Suandi,et al. Automated segmentation of iris images acquired in an unconstrained environment using HOG-SVM and GrowCut , 2017, Digit. Signal Process..
[5] Michele Nappi,et al. Mobile Iris Challenge Evaluation (MICHE)-I, biometric iris dataset and protocols , 2015, Pattern Recognit. Lett..
[6] Roger Clarke,et al. Human Identification in Information Systems , 1994 .
[7] Andrew Zisserman,et al. Three things everyone should know to improve object retrieval , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[8] Kiran B. Raja,et al. Smartphone based visible iris recognition using deep sparse filtering , 2015, Pattern Recognit. Lett..
[9] Alice J. O'Toole,et al. FRVT 2006 and ICE 2006 Large-Scale Experimental Results , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] Reza Derakhshani,et al. OcularNet: Deep Patch-based Ocular Biometric Recognition , 2018, 2018 IEEE International Symposium on Technologies for Homeland Security (HST).
[11] Reza Derakhshani,et al. Gender prediction from mobile ocular images: A feasibility study , 2017, 2017 IEEE International Symposium on Technologies for Homeland Security (HST).
[12] Jitendra Malik,et al. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[13] M. Angela Sasse,et al. Red-Eye Blink, Bendy Shuffle, and the Yuck Factor: A User Experience of Biometric Airport Systems , 2007, IEEE Security & Privacy.
[14] Kaushik Roy,et al. Data augmentation in CNN-based periocular authentication , 2016, 2016 6th International Conference on Information Communication and Management (ICICM).
[15] Andrey Nikiforov,et al. Combining iris and periocular biometric for matching visible spectrum eye images , 2017, Pattern Recognit. Lett..
[16] Basilio Sierra,et al. Iris matching by means of Machine Learning paradigms: A new approach to dissimilarity computation , 2017, Pattern Recognit. Lett..
[17] Mark J. Burge,et al. Handbook of Iris Recognition , 2013, Advances in Computer Vision and Pattern Recognition.
[18] Luís A. Alexandre,et al. Introduction to the Special Issue on the Recognition of Visible Wavelength Iris Images Captured At-a-distance and On-the-move , 2012, Pattern Recognit. Lett..
[19] Hugo Proença,et al. Insights into the results of MICHE I - Mobile Iris CHallenge Evaluation , 2018, Pattern Recognit..
[20] Yang Hu,et al. Improving colour iris segmentation using a model selection technique , 2015, Pattern Recognit. Lett..
[21] John Daugman,et al. High Confidence Visual Recognition of Persons by a Test of Statistical Independence , 1993, IEEE Trans. Pattern Anal. Mach. Intell..
[22] H. Proenca,et al. The NICE.I: Noisy Iris Challenge Evaluation - Part I , 2007, 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems.
[23] Kuntal Dey,et al. A preliminary study of CNNs for iris and periocular verification in the visible spectrum , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[24] Andrea F. Abate,et al. A Lightweight Mamdani Fuzzy Controller for Noise Removal on Iris Images , 2017, ICIAP.
[25] Xiaoqing Yu,et al. Eye landmarks detection via two-level cascaded CNNs with multi-task learning , 2018, Signal Process. Image Commun..
[26] Michal Haindl,et al. Unsupervised detection of non-iris occlusions , 2015, Pattern Recognit. Lett..
[27] John Daugman,et al. How iris recognition works , 2002, IEEE Transactions on Circuits and Systems for Video Technology.
[28] Andrey Nikiforov,et al. Using fusion of iris code and periocular biometric for matching visible spectrum iris images captured by smart phone cameras , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[29] Basilio Sierra,et al. Machine Learning approach to dissimilarity computation: Iris matching , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[30] Anil K. Jain,et al. Soft Biometric Traits for Personal Recognition Systems , 2004, ICBA.
[31] Hanyuan Zhang,et al. Batch process fault detection and identification based on discriminant global preserving kernel slow feature analysis. , 2018, ISA transactions.
[32] Jiquan Ngiam,et al. Sparse Filtering , 2011, NIPS.
[33] Javier Lorenzo-Navarro,et al. Local descriptors fusion for mobile iris verification , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[34] Ashok A. Ghatol,et al. Iris recognition: an emerging biometric technology , 2007 .
[35] Andreas Uhl,et al. Identifying the origin of Iris images based on fusion of local image descriptors and PRNU based techniques , 2017, 2017 IEEE International Joint Conference on Biometrics (IJCB).
[36] Sharath Pankanti,et al. An identity-authentication system using fingerprints , 1997, Proc. IEEE.
[37] Luís A. Alexandre,et al. The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[38] Jean-Luc Dugelay,et al. Fusing iris colour and texture information for fast iris recognition on mobile devices , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[39] Tieniu Tan,et al. DeepIris: Learning pairwise filter bank for heterogeneous iris verification , 2016, Pattern Recognit. Lett..
[40] Gil Melfe Mateus Santos,et al. Fusing iris and periocular information for cross-sensor recognition , 2015, Pattern Recognit. Lett..
[41] K.W. Bowyer,et al. The Iris Challenge Evaluation 2005 , 2008, 2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems.
[42] Javier Lorenzo-Navarro,et al. Periocular and iris local descriptors for identity verification in mobile applications , 2017, Pattern Recognit. Lett..
[43] Michele Nappi,et al. IS_IS: Iris Segmentation for Identification Systems , 2010, 2010 20th International Conference on Pattern Recognition.
[44] Michele Nappi,et al. Multimodal authentication on smartphones: Combining iris and sensor recognition for a double check of user identity , 2016, Pattern Recognit. Lett..
[45] Modesto Castrillón Santana,et al. Deep learning for source camera identification on mobile devices , 2017, Pattern Recognit. Lett..
[46] Jos B. T. M. Roerdink,et al. The Watershed Transform: Definitions, Algorithms and Parallelization Strategies , 2000, Fundam. Informaticae.
[47] Yung-Hui Li,et al. An Accurate and Efficient User Authentication Mechanism on Smart Glasses Based on Iris Recognition , 2017, Mob. Inf. Syst..
[48] Fatimah Khalid,et al. Noncircular iris segmentation based on weighted adaptive hough transform using smartphone database , 2018 .
[49] Andrew S. Patrick,et al. Usability and Acceptability of Biometric Security Systems , 2004, Financial Cryptography.
[50] Kuntal Dey,et al. Convolutional neural networks for ocular smartphone-based biometrics , 2017, Pattern Recognit. Lett..
[51] Michele Nappi,et al. Combining Hardwaremetry and Biometry for Human Authentication via Smartphones , 2015, ICIAP.
[52] Tieniu Tan,et al. Ordinal Feature Selection for Iris and Palmprint Recognition , 2014, IEEE Transactions on Image Processing.
[53] Xiaobo Zhang,et al. Noisy iris image matching by using multiple cues , 2012, Pattern Recognit. Lett..
[54] Jean-Luc Dugelay,et al. FIRE: Fast Iris REcognition on mobile phones by combining colour and texture features , 2017, Pattern Recognit. Lett..
[55] Kang Ryoung Park,et al. Deep Learning-Based Iris Segmentation for Iris Recognition in Visible Light Environment , 2017, Symmetry.
[56] Wai Lok Woo,et al. Sclera recognition: on the quality measure and segmentation of degraded images captured under relaxed imaging conditions , 2017, IET Biom..
[57] Miroslav Goljan,et al. Digital camera identification from sensor pattern noise , 2006, IEEE Transactions on Information Forensics and Security.
[58] Antonio Torralba,et al. Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.
[59] Andrea F. Abate,et al. SKIPSOM: Skewness & kurtosis of iris pixels in Self Organizing Maps for iris recognition on mobile devices , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[60] Ajita Rattani,et al. Ocular biometrics in the visible spectrum: A survey , 2017, Image Vis. Comput..
[61] Sacha Brostoff,et al. Transforming the ‘Weakest Link’ — a Human/Computer Interaction Approach to Usable and Effective Security , 2001 .
[62] Kiran B. Raja,et al. Multi-patch deep sparse histograms for iris recognition in visible spectrum using collaborative subspace for robust verification , 2017, Pattern Recognit. Lett..
[63] Kang Ryoung Park,et al. Noisy Ocular Recognition Based on Three Convolutional Neural Networks , 2017, Sensors.
[64] Hugo Proença,et al. Results from MICHE II - Mobile Iris CHallenge Evaluation II , 2017, Pattern Recognit. Lett..
[65] Andrea F. Abate,et al. Kurtosis and skewness at pixel level as input for SOM networks to iris recognition on mobile devices , 2017, Pattern Recognit. Lett..
[66] Stefano Ricciardi,et al. Ubiquitous iris recognition by means of mobile devices , 2015, Pattern Recognit. Lett..
[67] Andrea F. Abate,et al. BIRD: Watershed Based IRis Detection for mobile devices , 2015, Pattern Recognit. Lett..