Design of Multimodal Biometric Information Management System Based on Commercial Systems
In these years, Biometric technology has passed through its establishment and maintains a good momentum of growth. With the development and reform of social transformation, it seems almost inevitable that the public safety issues have increasingly become a focus. Biometric technology can effectively prevent infringement, obtain the criminal evidence and maintain the public safety. Many standards related to biometric identification in public security area are about to be implemented. Biometric identification will exploit better development opportunities. However, unimodal biometric may not be able to achieve the desired requirement for public security, especially for criminal in the civilian law enforcement environment. It has been found that unimodal biometric shows some inherent drawbacks in universality and accuracy. Hence, this paper proposes the design of multimodal biometric information management system (MBIMS) to create a collaborative platform by acquiring biometric data from multi-commercial systems, defines the data flow API and applies the prototype system successfully in the field of public security.
KeywordsBiometric Personal identification System fusion Public security
This work was supported in part by Shanghai Public Security Bureau and by Shanghai Municipal People’s Government. We also wish to express thanks to Jiangsu Qingtian Information Technology Co., Ltd.
- 3.Raju, A., Udayashankara, V.: Biometric person authentication: a review. In: 2014 International Conference on Contemporary Computing and Informatics (IC3I), pp. 575–580. IEEE (2014)Google Scholar
- 4.Kadam, A., Ghadi, M., Chavan, A., Jawale, P., Student, B.: Multimodal biometric fusion. Int. J. Eng. Sci. 12554 (2017)Google Scholar
- 5.Ghayoumi, M.: A review of multimodal biometric systems: fusion methods and their applications. In: 2015 IEEE/ACIS 14th International Conference on Computer and Information Science (ICIS), pp. 131–136. IEEE (2015)Google Scholar
- 6.Geng, A.-L., Liu, L.: The investigation on multimodal biometric recognition (2015)Google Scholar
- 9.Oliveira, E.L., Lima, C.A., Peres, S.M.: Fusion of face and gait for biometric recognition: systematic literature review. In: Proceedings of the XII Brazilian Symposium on Information Systems on Brazilian Symposium on Information Systems: Information Systems in the Cloud Computing Era, vol. 1, p. 15. Brazilian Computer Society (2016)Google Scholar
- 10.Gowda, H.S., Kumar, G.H., Imran, M.: Robust multimodal biometric verification system based on face and fingerprint. In: 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 243–247. IEEE (2017)Google Scholar
- 13.Shobana, D., Logeshwari, A., Maheswari, S.U.: A study on multimodal biometrics system (2017)Google Scholar
- 15.Shanmugasundaram, K., Mohamed, A.S.A., Ruhaiyem, N.I.R.: An overview of hand-based multimodal biometrie system using multi-classifier score fusion with score normalization. In: 2017 International Conference on Signal Processing and Communication (ICSPC), pp. 53–57. IEEE (2017)Google Scholar
- 16.Kumar, D.: A review in various approaches of feature extraction and feature fusion in multimodal biometric system IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 40(4), 384–395 (2017)Google Scholar
- 17.Gupta, K.: Advances in multi modal biometric systems: a brief review. In: 2017 International Conference on Computing, Communication and Automation (ICCCA), pp. 262–267. IEEE (2017)Google Scholar
- 18.Kumar, K., Farik, M.: A review of multimodal biometric authentication systems. Int. J. Sci. Technol. Res. 5, 12 (2016)Google Scholar
- 20.Beck, M.B., Rouchka, E.C., Yampolskiy, R.V.: Finding data in DNA: computer forensic investigations of living organisms. In: Rogers, M., Seigfried-Spellar, K.C. (eds.) ICDF2C 2012. LNICST, vol. 114, pp. 204–219. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-39891-9_13CrossRefGoogle Scholar