Person Identification Using Face, Ear and Foot Modalities at Rank Level

Snehlata Barde*, Zadgaonkar**
* Assistant Professor, Master of Computer Application Department, Shri Shankaracharya Group of Institutions, Bhilai, India.
** Professor and Vice Chancellor, CV Raman University, Bilaspur, India.
Periodicity:June - August'2014
DOI : https://doi.org/10.26634/jcom.2.2.3228

Abstract

Person recognition is a necessary requirement in government sector and private organization. AADHAR card is an application software used for person identification based on biometrics field since biometrics may be used to ensure that a person is authenticated. Multimodal biometric is a combination of two or more biometrics that helps to remove the limitation of a single biometric trait or an achievement of multimodal biometric person identification by means of combining deferent biometrics modalities like face, ear, iris, finger prints palm prints and foot. This paper worked on three modalities face, ear and foot for calculating results at rank level. For this, the authors have calculated Weight score of each modalities using different classifiers for face, PCA based neural network classifier, for Ear Eigen images and for foot modified sequential harr transform. After that the authors applied logistic regression method on fused data and calculated results that gave better result as compared to others. All works were performed on self created database of 100 persons.

Keywords

Principal Component Analysis (PCA), Eigen Image, Modified Sequential Harr Transform, Multimodal Biometrics, Eigen Ears, Euclidian Distance.

How to Cite this Article?

Barde, S., and Zadgaonkar, A.S. (2014). Person Identification Using Face, Ear and Foot Modalities at Rank Level. i-manager’s Journal on Computer Science, 2(2), 1-8. https://doi.org/10.26634/jcom.2.2.3228

References

[1]. R. Arun, Jain Anil, et al. (2004). “Multimodal th Biometrics: An Overview[C]”, Proceedings of 12 European Processing Conference, pp.1221-1224 (Vienna, Austria).
[2]. A. Ross, A.K. Jain, et al. (2003). “Information fusion in biometrics”, Pattern Recognition Letters, Vol. 24(13), pp. 2115 –2125.
[3]. M. Turk, A. Pentland et al. (1991). “Eigenfaces for recognition”, Journal of Cognitive Science. Vol. 3(1), pp. 71-86.
[4]. D.R. Kisku, J. K. Singh, M. Tistarelli, et al. (2009). “Multisensor biometric evidence fusion for person authentication using wavelet decomposition and monotonic decreasing graph[C]”, Proceedings of 7 International Conference on advances in Pattern Recognition (ICAPR), pp. 205-208 (Kolkata, India).
[5]. W. Zhao, R. Chellappa, A. Rosenfeld, P. J. Phillips, et al. (2003). “Face Recognition [J]”, An ACM Computing Surveys, Vol. 35(4), pp. 399-458.
[6]. X. Y. Jing, Y.F. Yao, J.Y. Yang, M. Li, D. Zhang et al. (2007). “Face and palm print pixel level fusion and kernel DCVRBF classifier for small sample biometric recognition”, Pattern Recognition, Vol.40(3), pp.3209-3224.
[7]. Cappelli, R., Maio. D, Maltoni et al. (2000). “Combining fingerprint classifiers”, Workshop on Multiple Classifier Systems, Vol.35(1), pp. 351–361.
[8]. L. Hong and A. K. Jain et al. (1998). “Integrating faces and fingerprints for personal identification”, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 20(12), pp. 1295–1307.
[9]. R. Frischholz and U. Dieckmann et al. (2000). “BiolD: A multimodal biometric identification system,” Computer, Vol. 33(2), pp. 64–68.
[10]. J. Fierrez-Aguilar, J. Ortega-Garcia, D. Garcia- Romero, and J. Gonzalez-Rodriguez et al. (2003). “A comparative evaluation of fusion strategies for th multimodal biometric verification”, in Proc. 4 Int. Conf. Audio- Video-Based Biometric Person Authentication, pp. 830–837.
[11]. A. Ross, R. Govindarajan et al. (2004). “Feature level fusion using hand and face biometrics[C]”. Proceedings of SPIE Conference on Biometric Technology for Human Identification, pp. 196 –204.
[12]. T. Wang, T. Tan, and A. K. Jain et al. (2003). “Combining face and iris biometrics for identity verification”, in Proc. 4 Int. Conf. Audio- Video-Based Biometric Person Authentication, LNCS 2688, pp. 805–813.
[13]. K. A. Toh, X. D. Jiang, and W. Y. Yau et al. (2004). “Exploiting global and local decisions for multi-modal biometrics verification”, IEEE Trans. Signal Process., Vol. 52(10), pp. 3059–3072.
[14]. R. Snelick, U. Uludag, A. Mink, et al. (2005). “Large scale evaluation of multimodal biometric authentication using state-of the-art systems”, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 27(3), pp. 450–455.
[15]. A. K. Jain, K. Nandakumar, and A. Ross, (2005). “Score normalization in multimodal biometric systems,” Pattern Recognition. Vol. 38(12), pp. 2270–2285.
[16]. W. Kong, D. Zhang et al. (2001). “Accurate iris segmentation based on novel reflection and eyelash detection model,” Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing, (Hong Kong)
[17]. D.R. Kisku, J. K. Singh, M. Tistarelli, et al. (2009). “Multisensor biometric evidence fusion for person authentication using wavelet decomposition and monotonic decreasing graph[C],” Proceedings of 7 International Conference on Advances in Pattern Recognition (ICAPR), pp. 205-208.
[18]. G.R. Sinha, Kavita Thakur, et al. (2010). “Modified PCA based Noise reduction of CFA images,” Journal of Science, Technology & Management, Vol. 1(2), pp. 60-67.
[19]. Snehlata, G.R.Sinha ET al. (2014). “PCA based Multimodal Biometrics using Ear and Face Modalities [J],” International Journal of Information Technology and Computer Science (IJITCS), Vol. 6(5), pp. 43-49.
[20]. Snehlata, G.R.Sinha et al. (2014). “Multimodal Biometrics using Face, Ear and Iris Modalities[c],” International Journal of Computer Applications Recent Advances in Information Technology NCRAIT, Vol.2, pp.9- 15.
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