International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 8, No. 3, 8 Mar. 2016
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Biometric Person Identification System: A Multimodal Approach Employing Spectral Graph Characteristics of Hand Geometry and Palmprint
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Author(s)
Index Terms
Hand geometry, Palmprint, Feature level fusion, Graph representation, Spectral graph properties, Hu moments, Support vector machine
Abstract
Biometric authentication systems operating in real world environments using a single modality are found to be insecure and unreliable due to numerous limitations. Multimodal biometric systems have better accuracy and reliability due to the use of multiple biometric traits to authenticate a claimed identity or perform identification. In this paper a novel method for person identification using multimodal biometrics with hand geometry and palmprint biometric traits is proposed. The geometrical information embedded in the user hand and palmprint images are brought out through the graph representations. The topological characterization of the image moments, represented as the virtual nodes of the palmprint image graph is a novel feature of this work. The user hand and palmprint images are represented as weighted undirected graphs and spectral characteristics of the graphs are extracted as features vectors. The feature vectors of the hand geometry and palmprint are fused at feature level to obtain a graph spectral feature vector to represent the person. User identification is performed by using a multiclass support vector machine (SVM) classifier. The experimental results demonstrate, an appreciable performance giving identification rate of 99.19% for multimodal biometric after feature level fusion of hand geometry and palmprint modalities. The performance is investigated by conducting the experiments separately for handgeometry, palmprint and fused feature vectors for person identification. Experimental results show that the proposed multimodal system achieves better performance than the unimodal cues, and can be used in high security applications. Further comparison show that it is better than similar other multimodal techniques.
Cite This Paper
Shanmukhappa A. Angadi, Sanjeevakumar M. Hatture, "Biometric Person Identification System: A Multimodal Approach Employing Spectral Graph Characteristics of Hand Geometry and Palmprint", International Journal of Intelligent Systems and Applications(IJISA), Vol.8, No.3, pp.48-58, 2016. DOI:10.5815/ijisa.2016.03.06
Reference
[1]Kuncheva L. I, Whitaker C. J, Shipp C. A and Duin R. P. W, 2000, “Is independence good for combining classifiers?,” Procedings of International Conference on Pattern Recognition (ICPR), Vol. 2, (Barcelona, Spain), pp. 168–171, 2000.
[2]Hong L and Jain A. K, 1998, “Integrating faces and fingerprints for personal identification,” IEEE Transactions on PAMI, vol. 20, pp. 1295–1307, Dec 1998.
[3]Donatello Conte, Pasquale Foggia, Carlo Sansone, Mario Vento, 2007, “How and Why Pattern Recognition and Computer Vision Applications Use Graphs,” Applied Graph Theory in Computer Vision and Pattern Recognition, Vol. 52, pp. 85-135, 2007.
[4]Ross, A.K. Jain, 2004,“Multimodal Biometrics: an Overview”, Proceedings of 12th European Signal Processing Conference, Vienna, Austria, pp. 1221-1224 , 2004.
[5]Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kanta Sing, " Multibiometrics Feature Level Fusion by Graph Clustering", International Journal of Security and Its Applications, Vol. 5, No. 2, April 2011.
[6]Rashmi Singhal, Narender Singh, Payal Jain, 2012, “Towards an Integrated Biometric Technique,” International Journal of Computer Applications, Vol. 42, No.13, pp. 20-23, March 2012.
[7]Yufei Han, Tieniu Tan, Zhenan Sung, "Palmprint Recognition Based on Directional Features and Graph Matching", Book section in Advances in Biometrics, Ed by Seon-Whan Lee and Stan Li, pp. 1164-1173, 2007.
[8]Wang H. and Hancock E.R, 2004, “A Kernel View of Spectral Point Pattern Matching,” Procedings of International Workshops on Advances in Structural and Syntactic Pattern Recognition and Statistical Techniques in Pattern Recognition, pp. 361-369, 2004.
[9]Yang Jian, Yang Jing-yu, Zhang David and Lu Jian-feng, 2003, “Feature fusion: parallel strategy vs. serial strategy,” Pattern Recognition, Vol. 36, No. 6, pp. 1961-1971, 2003.
[10]Karki Maya, Sethu Selvi S, 2013, “Multimodal Biometrics at Feature Level Fusion using Texture Features,” International Journal of Biometrics and Bioinformatics (IJBB), Vol.7, Issue 1, pp. 58-73, 2013.
[11]Gupta Aditya, Walia Ekjok, Vaidya Mahesh, 2014, “Feature level fusion of face, palm vein and palm print modalities using Discrete Cosine Transform” IEEE Proceedings on International Conference on Advances in Engineering and Technology Research (ICAETR), pp. 1-5, 2014.
[12]Nandakumar K. and Jain A. K., 2008, "Multibiometric Template Security using Fuzzy Vault," In Proceedings of IEEE Second International Conference on Biometrics: Theory, Applications and Systems, 2008.
[13] Deshmukh A,Pawar S and Joshi M, 2013, “Feature Level Fusion of Face And Fingerprint Modalities Using Gabor Filter Bank,” IEEE International Conference on Signal Processing, Computing and Control (ISPCC), pp.1-5, 2013.
[14]Mhaske, V.D., Patankar, A.J., 2013, “Multimodal biometrics by integrating fingerprint and palmprint for security,” IEEE International Conference on Computational Intelligence and Computing Research (ICCIC),pp. 1-5, 2013.
[15]Ajay Kumar, David Zhang, 2006, “Personal Recognition Using Hand Shape and Texture,” IEEE Image Processing, Vol. 15, No.8, pp. 2454-2461, 2006.
[16]Han C.C, 2004, “A hand-based personal authentication using a coarse-to fine Strategy”, Image and Vision Computing, Vol. 22, Issue. 11, pp. 909–918, 2004.
[17]Dewi Yanti Liliana, Eries Tri Utaminingsih, 2012, “The combination of palm print and hand geometry for biometrics palm recognition,” International Journal of Video & Image Processing and Network Security, Vol. 12, No.1, pp.1-5, 2012.
[18]Swapnali G. Garud, K.V. Kale, 2014, “Palmprint and Handgeometry Recognition using FAST features and Region properties,” International Journal of Science and Engineering Applications,Vol. 3 Issue 4, pp. 75-82, 2014.
[19]Quan-Sen Sun, Sheng-Gen Zeng, Pheng-Ann Heng and De-Sen Xia, 2005 “The Theory of Canonical Correlation Analysis and Its Application to Feature Fusion (in Chinese),”Chinese Journal of Computers, Vol. 28, No. 9, pp. 1524-1533, 2005.
[20]Nandakumar K, 2008, "Multibiometric Systems: Fusion Strategies and Template Security," Ph.D. Thesis, Michigan State University, USA, 2008.
[21]Miguel A. Ferrer, Aythami Morales, Carlos M. Travieso and Jesws B. Alonso, 2007, “Low Cost Multimodal Biometric identification System Based on Hand Geometry, Palm and Finger Textures,” 41 Annual IEEE International Carnahan Conference on Security Technologies ISBN:1-4244-1129-7, 52-58, 2007. Available from: (http://www.gpds.ulpgc.es).
[22]Zhang D., 2006, PolyU Palmprint Database, Biometric Research Centre, Hong Kong Polytechnic University, (Online) Available from: (http://www.comp.polyu.edu.hk/?biometrics/), 2006.
[23]Otsu N., 1978, “A threshold selection method from gray-scale histogram,” IEEE Transaction on SMC, 8, pp. 62-66, 1978.
[24]Gonzalez R.C. and Woods R.E., 2002, “Digital Image Processing using MATLAB”, Prentice-Hall, New Jersey, 2002.
[25]Shanmukhappa A. Angadi, Sanjeevakumar M. Hatture, 2011, “A Novel Spectral Graph Theoretic Approach To User Identification Using Hand Geometry,” International Journal of Machine Intelligence, Vol.3, No.4, pp. 282-288, 2011.
[26]Zhihu Huang, Jinsong Leng, 2010, “Analysis of Hu's Moment Invariants on Image Scaling and Rotation”, Proceedings of Second International Conference on Computer Engineering and Technology, pp. 476-480, 2010.
[27]Jin Soo Noh and Kang Hyeon Rhee, 2005, “Palmprint Identification Algorithm using Hu Invariant Moments and Otsu Binarization,” Proceedings of the Fourth Annual ACIS International Conference on Computer and Information Science, pp. 94-99, 2005.
[28]Arun Rossa and Rohin Govindarajan, 2005, "Feature Level Fusion Using Hand and Face Biometrics," Procedings of SPIE conference on Biometric Technology for Human Identification II, Vol.5779, pp. 196-204, 2005.
[29]Chih-Wei Hsu, Chih-Jen Lin, 2002,“A Comparison of Methods for Multiclass Support Vector Machines,” IEEE Transaction on Neural Networks, Vol. 13, No. 2, pp. 415-425, 2002.
[30]Ajay Kumar, David C. M. Wong, Helen C. Shen, Anil K. Jain, 2004, "Personal verification using Palmprint and Hand Geometry Biometric," Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 2004.