A clustering method for automatic biometric template selection
The problem addressed in this paper is the template selection and update in biometrics based on clustering. Template selection is a reliable method to reduce the number of templates used in a biometric system to account for variations observed in a person's biometric data. An efficient method based on clustering with automatic selection 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 template selection.
clustering biometrics template selection prototype faces signatures