Abstract
Aiming at the accuracy and security of pattern recognition system, this paper proposes a quaternion based multi-modal recognition algorithm that is more accurate and safe than unimodal, and fuses more features than most existing methods. Our algorithm fuses four features that involve two linear features and two non-linear features of two kinds of modalities. We fuse features into quaternion and the process of recognition is dealt in quaternion field. The equal error rate (EER) and DET curves given by the experiment we did on Yale face database and PolyU palm print database show that the quaternion based algorithm we proposed improves the recognition rate observably.
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Bigun E, Bigun J, Duc B et al (1997) Expert conciliation for multimodal person authentication systems using bayesian statistics. In: Proceeding of 1st international conference on audio-and video-based biometric person authentication. Springer, Crans-Montana, Switzerland, pp 291–300
Hong L, Jain AK, Pankanti S (1999) Can multibiometric improve performance? In: Proceedings of IEEE workshop on automatic identification advanced technologies. IEEE, Morristown, NJ, USA, pp 59–64
Hong L, Jain AK (1998) Integrating faces and fingerprints for personal identification. In: Proceedings of 3rd Asian conference on computer vision. IEEE, Hong Kong, China, pp 1295–1307
Duc B, Bigiin ES, Bigiin CJ et al (1997) Fusion of audio and video information for multimodal person authentication. Pattern Recognit Lett 18(9):835–843
Verlinde P, Maitre G (1997) Decision fusion in a multimodal identity verification system using a multilinear classifier. Techical report, Idiap Research Institute, Martigny, Switzerland
Verlinde P, Chollet G (1998) Combining vocal and visual cues in an identity verification system using K-n based classifiers. In: Proceedings of IEEE workshop on multimedia signal processing. IEEE, Redondo Beach, CA, USA, pp 59–64
Bouchaffra D, Amira A (2008) Structural hidden Markov models for biometrics-fusion of face and fingerprint. Pattern Recognit 41(3):852–867
Ma H (2014) Research of recognition method based on the feature layer fusion of palmprint and hand vein. Tianjin University of Technology
Yang J, Yang J, Frangi A (2003) Combined Fisherfaces framework. Image Vis Comput 21(12):1037–1044
Jolliffe IT (1986) Principal component analysis. Springer, New York
Scholkopf B, Smola AJ, Muller KR (1998) Nonlinear component analysis as a kernel eigenvalue problem. Nerual Comput 10(5):1299–1319
Lang FN et al (2008) Obtain method of quaternion matrix orthogonal eigenvector set and its application in color face recognition. Acta Automatica Sinica 34(2):121–129
Acknowledgments
This work is supported by National Natural Science Foundation of China (no. 61201399), China Postdoctoral Science Foundation (no. 2012M511003), Project of Science and Technology of Heilongjiang Provincial Education Department (no. 12521418), Youth Foundation of Heilongjiang University (no. 201026), and Startup Fund for Doctor of Heilongjiang University.
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Chen, M., Meng, X., Wang, Z. (2015). Quaternion Fisher Discriminant Analysis for Bimodal Multi-feature Fusion. In: Abraham, A., Jiang, X., Snášel, V., Pan, JS. (eds) Intelligent Data Analysis and Applications. Advances in Intelligent Systems and Computing, vol 370. Springer, Cham. https://doi.org/10.1007/978-3-319-21206-7_41
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DOI: https://doi.org/10.1007/978-3-319-21206-7_41
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