The week's pick
Random Articles
Reseach Article
Feature Selection for Finger Knuckle Print-based Multimodal Biometric System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 38 - Number 10 |
| Year of Publication: 2012 |
| Authors: Madasu Hanmandlu, Jyotsana Grover |
10.5120/4725-6905
|
Madasu Hanmandlu, Jyotsana Grover . Feature Selection for Finger Knuckle Print-based Multimodal Biometric System. International Journal of Computer Applications. 38, 10 ( January 2012), 27-33. DOI=10.5120/4725-6905
Abstract
In this paper, feature level fusion of finger knuckle prints (FKP’s) is implemented. To overcome the curse of dimensionality, feature selection using the triangular norms is proposed. There has been no effort on feature selection using the t-norms in the literature. In this paper we address the problem of feature selection on the finger knuckle print using the t-norms. An unknown parameter in t-norms is learnt using Reinforced Hybrid evolutionary technique. Feature level fusion is performed by combining the significant features of all FKP’s. Results show an improvement in the accuracy when the features are selected by a divergence function derived from the new entropy function using t-norms on two pairs of training features taken at a time. Results of both identi?cation and veri?cation rates show a signi?cant improvement in the performance with feature level fusion.
References
- Md. Monirul Kabir, Md. Monirul Islam, Kazuyuki Murase, 2010. A new wrapper feature selection approach using neural network. Neurocomputing, vol. 73, no. 16-18, pp. 3273-3283.
- Noelia Sánchez-Maroño, Amparo Alonso-Betanzos, 2011. Combining functional networks and sensitivity analysis as wrapper method for feature selection. Expert Systems with Applications, vol. 38, no. 10, pp. 12930-12938.
- Sebastián Maldonado, Richard Weber, 2009. A wrapper method for feature selection using Support Vector Machines. Information Sciences, vol. 179, no. 13, pp. 2208-2217.
- Romero, E. , Sopena, J.M., 2008. Performing Feature Selection With Multilayer Perceptrons. IEEE Trans. Neural Networks, vol. 19, no. 3, pp. 431-441.
- Pablo Bermejo, Jose A. Gámez, Jose M. Puerta, 2011. A GRASP algorithm for fast hybrid (filter-wrapper) feature subset selection in high-dimensional datasets. Pattern Recognition Letters. vol. 32, no. 5, pp. 701-71, Apr. 2011.
- Huawen Liu, Jigui Sun, Lei Liu, Huijie Zhang, 2009. Feature selection with dynamic mutual information. Pattern Recognition, vol. 42, no. 7, pp. 1330-1339.
- Yumin Chen, Duoqian Miao, Ruizhi Wang, 2010. A rough set approach to feature selection based on ant colony optimization. Pattern Recognition Letters, vol. 31, no. 3, pp. 226-233.
- Susana M.Vieira, João M.C. Sousa, Uzay Kaymak, 2011. Fuzzy criteria for feature selection. Fuzzy Sets and Systems, vol. 189, no. 1, pp. 1-18.
- Timo Ojala , Matti Pietikäinen , Topi Mäenpää , 2002. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns. IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 24, no.7, pp. 971-987.
- Michael Goh Kah Ong, Tee Connie, Andrew Teoh Beng Jin, 2008. Touch-Less Palm Print Biometric System. 3rd International Conference on Computer Vision Theory and Applications, Madeira – Portugal, pp. 423-430 .
- V. Novák, W. Pedrycz, 1988. Fuzzy sets and t-norms in the light of fuzzy logic. International Journal of Man-Machine Studies, vol. 22, no. 2, pp. 113-127.
- Zhang L., Zhang David, Zhu H., 2010. Online finger-knuckle-print verification for personal authentication. Pattern Recognition, vol. 43, no. 7, pp. 2560-2571.
- Lin Zhang, Lei Zhang, David Zhang, Hailong Zhu, 2011. Ensemble of local and global information for finger-knuckle-print recognition. Pattern Recognition, vol. 44, no. 9, pp. 1990-1998.
- Morales, A., Travieso, C.M., Ferrer, M.A., Alonso, J.B., 2011. Improved finger-knuckle-print authentication based on orientation enhancement. Electronics Letters, vol. 47, no. 6, pp. 380-384.
- Ajay Kumar and Yingbo Zhou, 2009. Personal identification using finger knuckle orientation features. Electronic Letters, vol. 45, no. 20, pp. 1023–1025.
- Datta T, Misra I. S., 2008. Improved adaptive bacteria foraging Algorithm in optimization of antenna array for faster convergence. Electromagnetic Research C, vol. 1, pp.143-157, 2008.
- Wael Mansour Korani, 2008. Bacterial foraging oriented by particle swarm optimization strategy for PID tuning. Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation, Atlanta, USA ,pp. 1823- 1826.
- M. Hanmandlu and Anirban Das, 2011. Content-based Image Retrieval by Information Theoretic Measure. Defence Science Journal, vol. 61, no. 5, pp. 415-430.
- Myoung Soo Park and Jin Young Choi, 2009. Theoretical analysis on feature extraction capability of class-augmented PCA. Pattern Recognition, vol. 42, no. 11, pp. 2353-2362.
- Pasi Luukka , 2011. Feature selection using fuzzy entropy measures with similarity classifier. Expert Systems with Applications, vol. 38, no. 4, pp. 4600-4607.
- Cheng-Lung Huang and Jian-Fan Dun, 2008. A distributed PSO–SVM hybrid system with feature selection and parameter optimization. Applied Soft Computing, vol. 8, no. 4, pp. 1381-1391, 2008.
Index Terms
Keywords