|
|
- 2016
基于深度卷积神经网络的指纹纹型分类算法
|
Abstract:
摘要 传统指纹纹型分类算法的准确率直接受到相应特征提取算法的影响.在海量指纹库中，同类纹型指纹形态变化明显增大，不同类纹型界限变得模糊，仅通过人工定义的特征进行分类很难适应全部指纹数据.为解除纹型分类问题与人工定义的特征提取问题的耦合，提出一种直接在指纹原图上进行纹型识别的算法.利用卷积神经网络自动特征提取的能力从大量指纹数据中学习得到纹型特征，并通过对训练数据的设计使网络能够适应指纹的多样性，提升算法的鲁棒性.此外，多尺度网络模型平均方法使分类准确性得到进一步提升.在国际公开指纹数据集NIST DB4上测得纹型四分类准确率达94.2%.
| [1] | Bouvrie J. Notes on convolutional neural networks[J/OL].Neural Nets, 2006.[2016-02-25].http://people.csail.mit.edu/jvb/papers/cnn.tutorial_old.pdf. |
| [2] | Ciresan D C, Meier U, Gambardella L M, et al. Deep, big, simple neural nets for handwritten digit recogni-tion[J]. Neural Computation, 2010, 22(12):3207-3220. |
| [3] | Ciresan D C, Meier U, Gambardella L M, et al.Convolutional neural network committees for hand-written character classification[C]//Proceedings of the 2011 International Conference on Document Analysis and Recognition. IEEE Computer Society, 2011:1135-1139. |
| [4] | Ji S, Xu W, Yang M, et al. 3D convolutional neural net-works for human action recognition[J]. Pattern Anal-ysis and Machine Intelligence, IEEE Transactions on, 2013, 35(1):221-231. |
| [5] | Frassetto Nogueira R, de Alencar Lotufo R, Campos Machado R. Evaluating software-based fingerprint live-ness detection using convolutional networks and local binary patterns[C]//Biometric Measurements and Sys-tems for Security and Medical Applications (BIOM-S) Proceedings, 2014 IEEE Workshop on. IEEE, 2014:22-29. |
| [6] | Cao K, Jain A K. Latent orientation field estima-tion via convolutional neural network[C]//International Conference on Biometrics. IEEE, 2015:349-356. |
| [7] | Nair V, Hinton G E. Rectified linear units improve restricted boltzmann machines[C]//Proceedings of the 27th International Conference on Machine Learning (ICML-10). 2010:807-814. |
| [8] | Ciresan D, Giusti A, Gambardella L M, et al. Deep neural networks segment neuronal membranes in elec-tron microscopy images[C]//Advances in Neural Infor-mation Processing Systems. 2012:2843-2851. |
| [9] | Domingos P. A few useful things to know about machine learning[J]. Communications of the ACM, 2012, 55(10):78-87. |
| [10] | <p> Henry E R. Classification and uses of finger prints[M].3rd ed. London:HM Stationery Office, 1905. |
| [11] | Jia Y, Shelhamer E, Donahue J, et al. Caffe:convolutional architecture for fast feature embed-ding[C]//Proceedings of the ACM International Confer-ence on Multimedia. ACM, 2014:675-678. |
| [12] | Wilson C L, Candela G T, Watson C I. Neural network fingerprint classification[J]. Journal of Artificial Neural Networks, 1994, 1(2):203-228. |
| [13] | Yao Y, Frasconi P, Pontil M. Fingerprint classi-fication with combinations of support vector ma-chines[C]//Audio and Video Based Biometric Person Authentication. Springer Berlin Heidelberg, 2001:253-258. |
| [14] | Cao K, Pang L, Liang J, et al. Fingerprint classifica-tion by a hierarchical classifier[J]. Pattern Recognition, 2013, 46(12):3186-3197. |
| [15] | Jung H W, Lee J H. Noisy and incomplete fingerprint classification using local ridge distribution models[J]. Pattern Recognition, 2015, 48(2):473-484. |
| [16] | Liu M. Fingerprint classification based on singulari-ties[C]//Pattern Recognition, 2009. Chinese Conference on. IEEE, 2009:1-5. |
| [17] | Leung K C, Leung C H. Improvement of fingerprint re-trieval by a statistical classifier[J]. Information Foren-sics and Security, IEEE Transactions on, 2011, 6(1):59-69. |
| [18] | Luo J, Song D, Xiu C, et al. Fingerprint classification combining curvelet transform and gray-level cooccur-rence matrix[J]. Mathematical Problems in Engineering, 2014(7):1-15. |
| [19] | Lawrence S, Giles C L, Tsoi A C, et al. Face recogni-tion:a convolutional neural-network approach[J]. Neu-ral Networks, IEEE Transactions on, 1997, 8(1):98-113. |
| [20] | Watson C I, Wilson C L. NIST special database 4.Fingerprint Database, National Institute of Standards and Technology, 1992, 17:77. |
| [21] | Karu K, Jain A K. Fingerprint classification[J]. Pattern Recognition, 1996, 29(3):389-404. |
| [22] | Jain A K, Minut S. Hierarchical kernel fitting for fingerprint classification and alignment[C]//Pattern Recognition, 2002. Proceedings 16th International Conference on. IEEE, 2002, 2:469-473. |
| [23] | Hong J H, Min J K, Cho U K, et al. Fingerprint clas-sification using one-vs-all support vector machines dy-namically ordered with naive bayes classifiers[J]. Pat-tern Recognition, 2008, 41(2):662-671.</p> |
