Abstract
This paper presents a feature level fusion approach which uses the improved K-medoids clustering algorithm and isomorphic graph for face and palmprint biometrics. Partitioning around medoids (PAM) algorithm is used to partition the set of n invariant feature points of the face and palmprint images into k clusters. By partitioning the face and palmprint images with scale invariant features SIFT points, a number of clusters is formed on both the images. Then on each cluster, an isomorphic graph is drawn. In the next step, the most probable pair of graphs is searched using iterative relaxation algorithm from all possible isomorphic graphs for a pair of corresponding face and palmprint images. Finally, graphs are fused by pairing the isomorphic graphs into augmented groups in terms of addition of invariant SIFT points and in terms of combining pair of keypoint descriptors by concatenation rule. Experimental results obtained from the extensive evaluation show that the proposed feature level fusion with the improved K-medoids partitioning algorithm increases the performance of the system with utmost level of accuracy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ross, A., Jain, A.K., Qian, J.Z.: Information Fusion in Biometrics. In: Bigun, J., Smeraldi, F. (eds.) AVBPA 2001. LNCS, vol. 2091, pp. 354–359. Springer, Heidelberg (2001)
Kisku, D.R., Gupta, P., Sing, J.K.: Feature Level Fusion of Biometric Cues: Human Identification with Doddington’s Caricature. In: International Conference on Security Technology, Communications in Computer and Information Sciences, pp. 157–164. Springer, Heidelberg (2009)
Rattani, A., Kisku, D.R., Bicego, M., Tistarelli, M.: Feature Level Fusion of Face and Fingerprint Biometrics. In: 1st IEEE International Conference on Biometrics, Theory, Applications and Systems, pp. 1–6 (2007)
Ross, A., Nandakumar, K., Jain, A.K.: Handbook of Multibiometrics. Springer, Heidelberg (2006)
Jain, A.K., Ross, A., Prabhakar, S.: An Introduction to Biometric Recognition. IEEE Transactions on Circuits and Systems for Video Technology, Special Issue on Image- and Video-Based Biometrics 14(1), 4–20 (2004)
Yao, Y.-F., Jing, X.-Y., Wong, H.-S.: Face and Palmprint Feature Level Fusion for Single Sample Biometrics Recognition. Neurocomputing 70(7), 1582–1586 (2007)
Ross, A., Govindarajan, R.: Feature Level Fusion using Hand and Face Biometrics. In: SPIE Conference on Biometric Technology for Human Identification II, pp. 196–204 (2005)
Fu, Y., Ma, Z., Qi, M., Li, J., Li, X., Lu, Y.: A Novel User-specific Face and Palmprint Feature Level Fusion. In: 2nd International Symposium on Intelligent Information Technology Application, pp. 296–300 (2008)
Yan, Y., Zhang, Y.-J.: Multimodal Biometrics Fusion using Correlation Filter Bank. In: International Conference on Pattern Recognition, pp. 1–4 (2008)
Kisku, D.R., Rattani, A., Grosso, E., Tistarelli, M.: Face Identification by SIFT-based Complete Graph Topology. In: 5th IEEE International Workshop on Automatic Identification Advanced Technologies, pp. 63–68 (2007)
Jain, A.K., Feng, J.: Latent Palmprint Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(6), 1032–1047 (2009)
Whitney, H.: Congruent Graphs and the Connectivity of Graphs. Am. J. Math. 54, 160–168 (1932)
Zhang, O., Couloigner, I.: A New and Efficient K-Medoid Algorithm for Spatial Clustering. In: Gervasi, O., Gavrilova, M.L., Kumar, V., Laganá, A., Lee, H.P., Mun, Y., Taniar, D., Tan, C.J.K. (eds.) ICCSA 2005. LNCS, vol. 3482, pp. 181–189. Springer, Heidelberg (2005)
Lowe, D.G.: Object Recognition from Local Scale-invariant Features. In: International Conference on Computer Vision, pp. 1150–1157 (1999)
Theodoridis, S., Koutroumbas, K.: Pattern Recognition, vol. 855. Elsevier, Amsterdam (2006)
Horiuchi, T.: Colorization Algorithm using Probabilistic Relaxation. Image and Vision Computing 22(3), 197–202 (2004)
Dasarathy, B.V.: Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques. IEEE Computer Society Press, Los Alamitos (1991)
Kumar, A., Wong, D.C.M., Shen, H.C., Jain, A.K.: Personal verification using Palmprint and Hand Geometry Biometric. In: 4th International Conference on Audio- and Video-Based Biometric Authentication, pp. 668–675 (2003)
Kisku, D.R., Tistarelli, M., Sing, J.K., Gupta, P.: Face Recognition by Fusion of Local and Global Matching Scores using DS theory: An Evaluation with Uni-classifier and Multi-classifier Paradigm. In: IEEE Computer Vision and Pattern Recognition Workshop on Biometrics, pp. 60–65 (2009)
Ribarí, C.S., Fratríc, I.: A Biometric Identification System based on Eigenpalm and Eigenfinger Features. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(11), 1698–1709 (2005)
Dubes, R., Jain, A.K.: Clustering Techniques: The User’s Dilemma. Pattern Recognition 8(4), 247–260 (1976)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kisku, D.R., Gupta, P., Sing, J.K. (2010). Feature Level Fusion of Face and Palmprint Biometrics by Isomorphic Graph-Based Improved K-Medoids Partitioning. In: Kim, Th., Adeli, H. (eds) Advances in Computer Science and Information Technology. AST ACN 2010 2010. Lecture Notes in Computer Science, vol 6059. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13577-4_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-13577-4_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13576-7
Online ISBN: 978-3-642-13577-4
eBook Packages: Computer ScienceComputer Science (R0)