Fingerprint Indexing Based on Minutia Cylinder-Code and Deep Convolutional Feature
SONG Dehua1, FENG Jufu1
1.Key Laboratory of Machine Perception(Ministry of Education), Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871
Abstract In the typical fingerprint indexing method based on minutia cylinder-code(MCC) feature, the minutiae local structure is adequately taken into account. Since the global structure of fingerprint is ignored, the accuracy of fingerprint retrieval is limited. Therefore, deep convolutional neural network is employed to learn the global feature(deep convolutional feature) of fingerprint. Then, the MCC and deep convolutional feature are fused to improve the fingerprint indexing accuracy. Experiments are carried out to compare the proposed method with other prominent approaches on three benchmark databases. Besides, the property of deep convolutional feature is analyzed. Experimental results show that the proposed method effectively improves the accuracy of fingerprint indexing.
Fund:Supported by State Key Program of National Natural Science Foundation of China(No.61333015)
About author:: SONG Dehua, Ph.D. candidate. His research interests include machine learning, pattern recognition and computer vision.FENG Jufu(Corresponding author), Ph.D., professor. His research interests include image processing, pattern recognition, machine learning and biometric recognition.
[1] MALTONI D, MAIO D, JAIN A K, et al. Handbook of Fingerprint Recognition. Berlin, Germany: Springer, 2003. [2] CAPPELLI R, MAIO D, MALTONI D, A Multi-classifier Approach to Fingerprint Classification. Pattern Analysis and Applications, 2002, 5(2): 136-144. [3] LUMINI A, MAIO D, MALTONI D. Continuous versus Exclusive Classification for Fingerprint Retrieval. Pattern Recognition Letters, 1997, 18(10): 1027-1034. [4] DE BOER J, BAZEN A M, GEREZ S H. Indexing Fingerprint Databases Based on Multiple Features // Proc of the 12th Annual Workshop on Circuits, Systems and Signal Processing. Berlin, Germany: Springer, 2001: 300-306. [5] JIANG X D, LIU M H, KOT A C. Fingerprint Retrieval for Identification. IEEE Transactions on Information Forensics and Security, 2006, 1(4): 532-542. [6] LEUNG K C, LEUNG C H. Improvement of Fingerprint Retrieval by a Statistical Classifier. IEEE Transactions on Information Forensics and Security, 2011, 6(1): 59-69. [7] ZHOU W, HU J K, WANG S, et al. Fingerprint Indexing Based on Combination of Novel Minutiae Triplet Features // Proc of the International Conference on Network and System Security. Berlin, Germany: Springer, 2014: 377-388. [8] KHODADOUST J, KHODADOUST A M. Fingerprint Indexing Based on Expanded Delaunay Triangulation. Expert Systems with Applications, 2017, 81: 251-267. [9] KHODADOUST J, KHODADOUST A M. Fingerprint Indexing Based on Minutiae Pairs and Convex Core Point. Pattern Recognition, 2017, 67: 110-116. [10] CAPPELLI R, FERRARA M, MALTONI D. Fingerprint Indexing Based on Minutia Cylinder-Code. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(5): 1051-1057. [11] GYAOURAOV A A, ROSS A. A Novel Coding Scheme for Indexing Fingerprint Patterns // Proc of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition. Berlin, Germany: Springer, 2008: 755-764. [12] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. ImageNet Cla-ssification with Deep Convolutional Neural Networks // PEREIRA F, BURGES C J C, BOTTOV L, et al., eds. Advances in Neural Information Processing Systems 25. Cambridge, USA: The MIT Press, 2012: 1097-1105. [13] HINTON G E, SRIVASTAVA N, KRIZHEVSKY A, et al. Improving Neural Networks by Preventing Co-adaptation of Feature Detectors. Computer Science, 2012, 3(4): 212-223. [14] YANDEX A B, LEMPITSKY V. Aggregating Local Deep Features for Image Retrieval // Proc of the IEEE International Conference on Computer Vision. Washington, USA: IEEE, 2015: 1269-1277. [15] 江 璐.基于深度卷积神经网络的指纹特征提取算法研究.硕士学位论文.北京:中国科学院大学, 2016. (JIANG L. Exploiting Feature Extraction Algorithm of Fingerprint Based on Deep Convolutional Neural Network. Master Dissertation. Beijing, China: University of Chinese Academy of Sciences, 2016.) [16] CAPPELLI R, FERRARA M, MALTONI D. Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(12): 2128-2141. [17] CHIKKERUR S, CARTWRIGHT A N, GOVINDARAJU V. Fingerprint Image Enhancement Using STFT Analysis. Pattern Recognition, 2007, 40(1): 198-211.
2018, Vol. 31 
