Multilocal creaseness based on the level-set extrinsic curvature
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
A robust two step approach for fingerprint identification
Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Personal authentication using digital retinal images
Pattern Analysis & Applications
Similarity Metrics Analysis for Feature Point Based Retinal Authentication
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
IEEE Transactions on Information Technology in Biomedicine
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In this work a methodology for the classification of retinal feature points is applied to a biometric system. This system is based in the extraction of feature points, namely bifurcations and crossovers as biometric pattern. In order to compare a pattern to other from a known individual a matching process takes place between both points sets. That matching task is performed by finding the best geometric transform between sets, i.e. the transform leading to the highest number of matched points. The goal is to reduce the number of explored transforms by introducing the previous characterisation of feature points. This is achieved with a constraint avoiding two differently classified points to match. The empirical reduction of transforms is about 20%.