Feature-level Fusion of Palm Print and Palm Vein for Person Authentication Based on Entropy Technique
نویسندگان
چکیده
This paper presents a new approach to authenticate individuals using multiple biometric modalities. It deploys palm print and palm vein images for greater accuracy and flexibility. The contactless system uses a multispectral camera to capture the visible and Near Infrared Images (NIR) simultaneously. Subjects are allowed to place their hands freely below the camera. The Region of Interest (ROI) extraction method used is rotation and translational invariant. Different pre-processing techniques are used for noise reduction. We introduce a simple entropy based technique to extract the palm print and palm vein features. The feature level fusion adopted in this system uses least features (only 16). For 100 subject’s, distance based matching yields promising recognition rate (GAR) of 99%.
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