Abstract
Biometrics is the process of verifying or identifying an individual using the person’s physiological and behavioral characteristics such as face, fingerprint, iris, signature, and gait. The main advantage of using biometrics for recognition is that it is unique for every individual and cannot be misplaced or forgotten. However, biometric systems that use a single biometric trait have to contend with noisy data, restricted degrees of freedom, failure to-enroll problems, spoof attacks, and unacceptable error rates. Various researchers have suggested that no single biometric modality can provide the protection required for high security applications [1] - [4]. To alleviate this problem and enhance the performance of a biometric system, information from different biometric sources are combined and such systems are known as multimodal biometric systems [2].
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Singh, R., Vatsa, M., Noore, A. (2007). Intelligent Biometric Information Fusion using Support Vector Machine. In: Nachtegael, M., Van der Weken, D., Kerre, E.E., Philips, W. (eds) Soft Computing in Image Processing. Studies in Fuzziness and Soft Computing, vol 210. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-38233-1_12
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DOI: https://doi.org/10.1007/978-3-540-38233-1_12
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