參考文獻 |
[1] J. Daugman, “How Iris Recognition Works,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 1, pp. 21-30, JAN 2004.
[2] H. Proenca and L. A. Alexandre, “Iris Recognition: Analysis of the Error Rates Regarding the Accuracy of the Segmentation Stage,” Image and Vision Computing, vol. 28, no. 1, pp. 202-206, JAN 2010.
[3] H. Hofbauer, F. A.-Fernandez, J. Bigun, and A. Uhl, “Experimental Analysis Regarding the Influence of Iris Segmentation on the Recognition Rate,” The Institution of Engineering and Technology Biometrics, vol. 5, no. 3, pp. 200-211, AUG 2016.
[4] S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 6, pp. 1137-1149, JAN 2016.
[5] J. A. Bilmes, “A Gentle Tutorial of the EM Algorithm and Its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models,” Technical Report ICSI-TR-97-021, University of Berkeley, APR 1998.
[6] M. A. T. Figueiredo and A. K. Jain, “Unsupervised Learning of Finite Mixture Models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 3, pp. 381-396, MAR 2002.
[7] Y.-H. Li and P.-J. Huang, “An Accurate and Efficient User Authentication Mechanism on Smart Glasses based on Iris Recognition,” Mobile Information Systems, vol. 2017, Article ID 1281020, pp. 1-14, JUL 2017.
[8] R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation,” 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 580-587, OCT 2014.
[9] M. Everingham, L. V. Gool, C. K. I. Williams, J. Winn, and A. Zisserman, “The PASCAL Visual Object Classes (VOC) Challenge,” International Journal of Computer Vision, vol. 88, no. 2, pp. 303-338, JUN 2010.
[10] P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan, “Object Detection with Discriminatively Trained Part-based Models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 9, pp. 1627-1645, SEP 2010.
[11] A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet Classification with Deep Convolutional Neural Networks,” Advances in Neural Information Processing Systems 25, pp. 1097-1105, DEC 2012.
[12] K. He, X. Zhang, S. Ren, and J. Sun, “Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 9, pp. 1904-1916, JAN 2015.
[13] R. Girshick, “Fast R-CNN,” 2015 IEEE International Conference on Computer Vision, pp. 1440-1448, DEC 2015.
[14] J. R. R. Uijlings, K. E. A. van de Sande, T. Gevers, and A. W. M. Smeulders, “Selective Search for Object Recognition,” International Journal of Computer Vision, vol. 104, no. 2, pp. 154-171, SEP 2013.
[15] C. L. Zitnick and P. Dollar, “Edge Boxes: Locating Object Proposals from Edges,” European Conference on Computer Vision, pp. 391-405, SEP 2014.
[16] D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov, “Scalable Object Detection using Deep Neural Networks,” 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2155-2162, JUN 2014.
[17] C. Szegedy, S. Reed, D. Erhan, D. Anguelov, and S. Ioffe, “Scalable, High-Quality Object Detection,” arXiv 1412.1441v3, DEC 2015.
[18] J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, “You Only Look Once: Unified, Real-Time Object Detection,” 2016 IEEE Conference on Computer Vision and Pattern Recognition, pp. 779-788, JUN 2016.
[19] J. Daugman, “High Confidence Visual Recognition of Persons by A Test of Statistical Independence,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 11, pp. 1148-1161, NOV 1993.
[20] R. Wildes, “Iris Recognition: An Emerging Biometric Technology,” Proceedings of the IEEE, vol. 85, no. 9, pp. 1348-1363, SEP 1997.
[21] T. Tan, Z. He, and Z. Sun, “Efficient and Robust Segmentation of Noisy Iris Images for Non-Cooperative Iris Recognition,” Image and Vision Computing, vol. 28, no. 2, pp. 223-230, FEB 2010.
[22] Y. A.-Betancourt and M. G.-Silvente, “A Fast Iris Location based on Aggregating Gradient Approximation using QMA-OWA Operator,” International Conference on Fuzzy Systems, pp. 1-8, JUL 2010.
[23] J. I. Pelaez and J. M. Dona, “A Majority Model in Group Decision Making using QMA-OWA Operators,” International Journal of Intelligent Systems, vol. 21, no. 2, pp. 193-208, FEB 2006.
[24] H. Ghodrati, M. J. Dehghani, M. S. Helfroush, and K. Kazemi, “Localization of Noncircular Iris Boundaries using Morphology and Arched Hough Transform,” 2010 2nd International Conference on Image Processing Theory, Tools and Applications, pp. 458-463, JUL 2010.
[25] J. Canny, “A Computational Approach to Edge Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-8, no. 6, pp. 679-698, NOV 1986.
[26] X.-C. Wang and X.-M. Xiao, “An Iris Segmentation Method based on Difference Operator of Radial Directions,” 2010 6th International Conference on Natural Computation, pp. 135-138, AUG 2010.
[27] J. Liu, X. Fu, and H. Wang, “Iris Image Segmentation based on K-means Cluster,” 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, pp. 194-198, OCT 2010.
[28] F. Yan, Y. Tian, H. Wu, Y. Zhou, L. Cao, and C. Zhou, “Iris Segmentation using Watershed and Region Merging,” 2014 9th IEEE Conference on Industrial Electronics and Applications, pp. 835-840, JUN 2014.
[29] J. B. T. M. Roerdink and A. Meijster, “The Watershed Transform: Definitions, Algorithms and Parallelization Strategies,” Fundamenta Informaticae, vol. 41, no. 1-2, pp. 187-228, APR 2000.
[30] A. F. Abate, M. Frucci, C. Galdi, and D. Riccio, “BIRD: Watershed based Iris Detection for Mobile Devices,” Pattern Recognition Letters, vol. 57, pp. 41-49, MAY 2015.
[31] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active Contour Models,” International Journal of Computer Vision, vol. 1, no. 4, pp. 321-331, JAN 1988.
[32] A. A. Jarjes, K. Wang, and G. J. Mohammed, “Iris Localization: Detecting Accurate Pupil Contour and Localizing Limbus Boundary,” 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics, pp. 349-352, MAR 2010.
[33] G. J. Mohammed, B.-R. Hong, and A. A. Jarjes, “Accurate Pupil Features Extraction based on New Projection Function,” Computing and Informatics, vol. 29, no. 4, pp. 663-680, APR 2009.
[34] C. A. C. M. Bastos, I. R. Tsang, and G. D. C. Calvalcanti, “A Combined Pulling & Pushing and Active Contour Method for Pupil Segmentation,” 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 850-853, MAR 2010.
[35] Z. He, T. Tan, and Z. Sun, “Iris Localization via Pulling and Pushing,” 18th International Conference on Pattern Recognition, pp. 366-369, AUG 2006.
[36] V. N. Boddeti, B. V. K. V. Kumar, and K. Ramkumar, “Improved Iris Segmentation based on Local Texture Statistics,” 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers, pp. 2147-2151, NOV 2011.
[37] T. F. Chan and L. A. Vese, “Active Contours without Edges,” IEEE Transactions on Image Processing, vol. 10, no. 2, pp. 266-277, FEB 2001.
[38] E. Krichen, “Lef3a: Pupil Segmentation using Viterbi Search Algorithm,” 2012 5th IAPR International Conference on Biometrics, pp. 323-329, APR 2012.
[39] A. J. Viterbi, “Error Bounds for Convolutional Codes and An Asymptotically Optimum Decoding Algorithm,” IEEE Transactions on Information Theory, vol. 13, no. 2, pp. 260-269, APR 1967.
[40] R. Tang and S. Weng, “Improving Iris Segmentation Performance via Borders Recognition,” 2011 4th International Conference on Intelligent Computation Technology and Automation, pp. 580-583, MAR 2011.
[41] H. Li, Z. Sun, and T. Tan, “Robust Iris Segmentation based on Learned Boundary Detectors,” 2012 5th IAPR International Conference on Biometrics, pp. 317-322, APR 2012.
[42] J. Friedman, T. Hastie, and R. Tibshirani, “Additive Logistic Regression: A Statistical View of Boosting,” The Annals of Statistics, vol. 28, no. 2, pp. 337-407, APR 2000.
[43] D. Benboudjema, N. Othman, B. Dorizzi, and W. Pieczynski, “Challenging Eye Segmentation using Triplet Markov Spatial Models,” 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1927-1931, MAY 2013.
[44] W. Pieczynski, D. Benboudjema, and P. Lanchantin, “Statistical Image Segmentation using Triplet Markov Fields,” SPIE 4885 Image and Signal Processing for Remote Sensing VIII, SEP 2002.
[45] M. Happold, “Structured Forest Edge Detectors for Improved Eyelid and Iris Segmentation,” 2015 International Conference of the Biometrics Special Interest Group, pp. 28-33, SEP 2015.
[46] P. Dollar and C. L. Zitnick, “Structured Forests for Fast Edge Detection,” 2013 IEEE International Conference on Computer Vision, pp. 1841-1848, DEC 2013.
[47] K. W. Bowyer, K. P. Hollingsworth, and P. J. Flynn, “A Survey of Iris Biometrics Research: 2008-2010,” Handbook of Iris Recognition, pp. 15-54, New York: Springer, London, JAN 2013.
[48] M. R. Rajput and G. S. Sable, “IRIS Biometrics Survey 2010-2015,” 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology, pp. 2028-2033, MAY 2016.
[49] M. D. Zeiler and R. Fergus, “Visualizing and Understanding Convolutional Networks,” European Conference on Computer Vision, pp. 818-833, SPE 2014.
[50] K. Simonyan and A. Zisserman, “Very Deep Convolutional Networks for Large-Scale Image Recognition,” International Conference on Learning Representations, APR 2015.
[51] V. Nair and G. E. Hinton, “Rectified Linear Units Improve Restricted Boltzmann Machines,” Proceedings of the 27th International Conference on Machine Learning, pp. 807-814, JUN 2010.
[52] S. Ioffe and C. Szegedy, “Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift,” Proceedings of the 32nd International Conference on Machine Learning, vol. 37, pp. 448-456, JUL 2015.
[53] J. Long, E. Shelhamer, and T. Darrell, “Fully Convolutional Networks for Semantic Segmentation,” 2015 IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431-3440, JUN 2015.
[54] CASIA Iris Image Database, http://biometrics.idealtest.org/. |