Segmentation-Free Biometric Recognition Using Correlation Filters
Andres Rodriguez and B.V.K. Vijaya Kumar, Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, afrodrig@ece.cmu.edu, kumar@ece.cmu.edu
Abstract
In most biometric recognition studies, test biometric signatures (e.g., faces, irises, finger prints, etc.) are segmented from their background before they are compared to stored signatures. However, such segmentation is not easy to carry out in challenging imaging conditions. Here we show that correlation filters (CFs) can be used to avoid segmentation and achieve segmentation-free biometric recognition. CFs do not require the object of interest to first be localized or ...
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