Abstract
This paper summarizes the main characteristics of data fusion at different levels (sensor, features, scores and decisions). Although it is presented in the framework of biometric applications it is general for all the pattern recognition applications because this presentation is focused in the main blocks of a general pattern recognition system. Thus, the application in mind will imply a different sensor, feature extractor, classifier and decision maker but data fusion will be performed in a similar way.
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Faundez-Zanuy, M. (2009). Data Fusion at Different Levels. In: Esposito, A., Hussain, A., Marinaro, M., Martone, R. (eds) Multimodal Signals: Cognitive and Algorithmic Issues. Lecture Notes in Computer Science(), vol 5398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00525-1_9
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DOI: https://doi.org/10.1007/978-3-642-00525-1_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00524-4
Online ISBN: 978-3-642-00525-1
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