A Clustering Method for Automatic Biometric Template Selection

The problem addressed in this paper is the templateselection and update in biometrics based on clustering. Templateselection is a reliable method to reduce the number of templates used in abiometric system to account for variations observed in a person's biometric data. An efficient method based on clustering with automaticselection of the number of clusters is proposed in this work for finding subgroups of similar templates which are used for prototype selection. Experimental results confirm the advantage of the new method and the importance of adopting a procedure to perform templateselection.