Finger knuckleprint based recognition system using feature tracking
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Iris recognition using consistent corner optical flow
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Iris classification based on its quality
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories
A heuristic technique for performance improvement of fingerprint based integrated biometric system
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories
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This paper proposes a new powerful distance measure called Normalized Unmatched Points (NUP). This measure can be used in a face recognition system to discriminate facial images. It works by counting the number of unmatched pixels between query and database images. A face recognition system has been proposed which makes use of this proposed distance measure for taking the decision on matching. This system has been tested on four publicly available databases, viz. ORL, YALE, BERN and CALTECH databases. Experimental results show that the proposed measure achieves recognition rates more than 98.66% for the first five likely matched faces. It is observed that the NUP distance measure performs better than other existing similar variants on these databases.