Mohammed, F., ALdaidamony, E., Raid, A. (2015). IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES. International Journal of Intelligent Computing and Information Sciences, 15(1), 15-24. doi: 10.21608/ijicis.2015.10907
F Mohammed; E ALdaidamony; A Raid. "IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES". International Journal of Intelligent Computing and Information Sciences, 15, 1, 2015, 15-24. doi: 10.21608/ijicis.2015.10907
Mohammed, F., ALdaidamony, E., Raid, A. (2015). 'IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES', International Journal of Intelligent Computing and Information Sciences, 15(1), pp. 15-24. doi: 10.21608/ijicis.2015.10907
Mohammed, F., ALdaidamony, E., Raid, A. IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES. International Journal of Intelligent Computing and Information Sciences, 2015; 15(1): 15-24. doi: 10.21608/ijicis.2015.10907
IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES
Information Science Department , Faculty of Computers and Information System, Mansoura University - Egypt
Abstract
Individual identification process is a very significant process that resides a large portion of day by day usages. Identification process is appropriate in work place, private zones, banks …etc. Individuals are rich subject having many characteristics that can be used for recognition purpose such as finger vein, iris, face …etc. Finger vein and iris key-points are considered as one of the most talented biometric authentication techniques for its security and convenience. SIFT is new and talented technique for pattern recognition. However, some shortages exist in many related techniques, such as difficulty of feature loss, feature key extraction, and noise point introduction. In this manuscript a new method named SIFT-based iris and SIFT-based finger vein identification with normalization and enhancement is proposed for achieving better performance. In evaluation with other SIFT-based iris or SIFT-based finger vein recognition algorithms, the suggested technique can overcome the difficulties of accurate extraction of key-points and clear the noise points without feature loss. Experimental outcomes demonstrate that the normalization and improvement steps are critical for SIFT-based iris recognition and SIFT-based finger vein recognition , the recommended method can accomplish satisfactory recognition performance.
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