Tistarelli, Massimo and Grosso, Enrico and Lagorio, Andrea (2005) Spiral topologies for biometric recognition. In: Tistarelli, Massimo and Bigun, Josef and Grosso, Enrico (eds). Advanced studies in biometrics: Summer School on Biometrics, Alghero, Italy, June 2-6, 2003: revised selected lectures and papers. Berlin-Heidelberg, Springer. p. 69-90. (Lecture notes in computer science, 3161/2005). ISBN 978-3-540-26204-6. Book Section.
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Biometric recognition has attracted the attention of scientists, investors, government agencies as well as the media for the great potential in many application domains. It turns out that there are still a number of intrinsic drawbacks in all biometric techniques. In this paper we postulate the need for a proper data representation which may simplify and augment the discrimination among different instances or biometric samples of different subjects. Considering the design of many natural systems it turns out that spiral (circular) topologies are the best suited to economically store and process data. Among the many developed techniques for biometric recognition, face analysis seems to be the most promising and interesting modality. The ability of the human visual system of analyzing unknown faces, is an example of the amount of information which can be extracted from face images. Nonetheless, there are still many open problems which need to be faced as well. The choice of optimal resolution of the face within the image, face registration and facial feature extraction are still open issues. This not only requires to devise new algorithms but to determine the real potential and limitations of existing techniques. In this paper two different methods for face matching are presented, based on the same similarity measure but on different image representations. The methods are tested with conventional and also new databases, obtained from real subjects in real working environments.
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