Abstract
Biometrics provides a reliable authentication of a human in a wide variety of applications such as security systems, surveillance and human-computer interaction. Biometric system was started with utilization of a single biometric feature referring as a unimodal biometric system, which is unable to fulfill the security needs extensively in a highly sensitive environment and hence multibiometrics has emerged gaining more importance in the research area. Though there is a shortage of publicly available multimodal databases acquired in real unconstrained environment, a multimodal biometric system can succeed with the assistance of suitable multiple sensors providing higher accuracy rate than that of unimodal biometrics, of course subject to cost, time and subject’s acceptance This paper presents a new multimodal dataset which is developed using simple acquisition setup and devices to capture features belonging to the same person in uncontrolled scenarios. The dataset is composed of color images collected from 100 subjects (50 male and 50 female) under the age group 18–22. Totally 6 samples per trait were collected at different time internals between 2011 and 2014 with various occlusions. The dataset is also tested and analyzed by our developed biometric recognition system.
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Jain, A.K., Ross, A., Prabhakar, S.: An introduction to biometric recognition. Circ. Syst. Video Technol. IEEE Trans. on 14(1), 4–20 (2004)
Bigun, J., Fiérrez-Aguilar, J., Ortega-Garcia, J., Gonzalez-Rodriguez, J.: Combining biometric evidence for person authentication. In: Advanced Studies in Biometrics, pp. 1–18, Springer, Berlin Heidelberg (2005)
Ross, A., Jain, A.: Information fusion in biometrics. Pattern Recogn. Lett. 24(13), 2115–2125 (2003)
Poornima, S., Nasreen, F., Prakash, A.D.S., Raghuraman, A.: Versatile and economical acquisition setup for dorsa palm vein authentication. Procedia Comput. Sci. 50, 323–328 (2015)
Poornima, S, Subramanian, S.: Unconstrained iris authentication through fusion of RGB channel information. Int. J. Pattern Recogn. Artif. Intell. 28(5), 1–18, 1456010 (2014)
Proença, H., Alexandre, L.: Iris recognition: an analysis of the aliasing problem in the iris normalization stage. Int. Conf. Comput. Intell. Secur. 2, 1771–1774 (2006)
Daugman, J.: How iris recognition works. IEEE Trans. Circ. Syst. Video Technol. 14(1), 21–30 (2004)
Masek, L.: Recognition of human iris patterns for biometric identification. Doctoral Dissertation, Master’s Thesis, University of Western Australia (2003)
Wang, Q., Zhang, X., Li, M., Dong, X., Zhou, Q., Yin, Y.: Adaboost and multi-orientation 2D gabor-based noisy iris recognition. Pattern Recogn. Lett. 33(8), 978–983 (2012)
Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vis. 57(2), 137–154 (2004)
Kumar, A., Wu, C.: Automated human identification using ear imaging. Pattern Recogn. 45, 956–968 (2012)
Guo, Z., Zhang, L., Zhang, D., Mou, X.: Hierarchical multiscale LBP for face and palmprint recognition. In 17th IEEE International Conference on Image Processing (ICIP), pp. 4521–4524 (2010)
Poornima, S., Subramanian, S.: Personal authentication through dorsa palm vein patterns. Int. J. Appl. Eng. Res. 10(34), 27286–27290 (2015)
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Glad to thank the persons who contributed their feature images to build this versatile multimodal dataset with great cooperation.
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Poornima, S. (2016). Multimodal Database: Biometric Authentication for Unconstrained Samples. In: Satapathy, S., Das, S. (eds) Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 2. Smart Innovation, Systems and Technologies, vol 51. Springer, Cham. https://doi.org/10.1007/978-3-319-30927-9_29
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DOI: https://doi.org/10.1007/978-3-319-30927-9_29
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