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2D ear classification based on unsupervised clustering
2014
IEEE International Joint Conference on Biometrics
Ear classification refers to the process by which an input ear image is assigned to one of several pre-defined classes based on a set of features extracted from the image. In the context of large-scale ear identification, where the input probe image has to be compared against a large set of gallery images in order to locate a matching identity, classification can be used to restrict the matching process to only those images in the gallery that belong to the same class as the probe. In this
doi:10.1109/btas.2014.6996239
dblp:conf/icb/PflugBR14
fatcat:slzpunqrajdszgji6phjx7dysu