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Titlebook: Biometric Authentication; International ECCV 2 Massimo Tistarelli,Josef Bigun,Anil K. Jain Conference proceedings 2002 Springer-Verlag Berl

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發(fā)表于 2025-3-28 18:39:53 | 只看該作者
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發(fā)表于 2025-3-28 21:44:07 | 只看該作者
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發(fā)表于 2025-3-29 02:54:41 | 只看該作者
Monolayers and Multilayers of Biomolecules,chnique described here obviates the need for extracting minutiae points or the core point to either align or match fingerprint images. The proposed scheme examines the ridge strength (in local neighborhoods of the fingerprint image) at various orientations, using a set of 8 Gabor filters, whose spat
44#
發(fā)表于 2025-3-29 04:30:49 | 只看該作者
https://doi.org/10.1007/978-1-4899-3716-2 have been in use in forensic applications for many years and, more recently, in computer-automated identification and authentication. For automated fingerprint image matching, a machine representation of a fingerprint image is often a set of minutiae in the print; a minimal, but fundamental, repres
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發(fā)表于 2025-3-29 08:50:50 | 只看該作者
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發(fā)表于 2025-3-29 15:05:30 | 只看該作者
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發(fā)表于 2025-3-29 16:31:21 | 只看該作者
48#
發(fā)表于 2025-3-29 20:19:59 | 只看該作者
https://doi.org/10.1057/9780230109865ep during the design of the system is the choice of an appropriate edge model that fits for a wide range of different human faces. In this paper we present an optimization approach that creates and successively improves such a model by means of genetic algorithms. To speed up the process and to prev
49#
發(fā)表于 2025-3-30 03:35:43 | 只看該作者
https://doi.org/10.1057/9780230109865proach starts from a coarse segmentation which provides regions of homogeneous statistical color distribution. Some regions represent parts of human skin and are selected by minimizing an error between the color distribution of each region and the output of a compression decompression neural network
50#
發(fā)表于 2025-3-30 05:39:07 | 只看該作者
Nausicaa Pouscoulous,Ira A. Noveckface recognition can be performed using template matching or a feature-based-approach, but both these methods suffer from occlusion and require an a priori model for extracting information. To avoid these drawbacks, we present in this paper a complete scheme for face recognition based on salient fea
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