Title
Local Invariant Representation For Multi-Instance Toucheless Palmprint Identification
Abstract
Palmprint identification is a popular biometric technology used for personal characterization. Traditional palmprint recognition methods are mostly based on acquisition devices with contact, and this, may affect their user friendliness. In this paper, a toucheless palmprint identification method based on Scale Invariant Feature Transform (SIFT) descriptors and sparse representation method is proposed, in order to extract palmprint features of left and right palms. The fusion scheme is performed at rank level using Support Vector Machines (SVM) classifier and probability distribution to generate the final identity of a person. Experiments evaluated on CASIA palmprint database and a proposed toucheless REST (REgim Sfax Tunisia) hand database, report promising performances which are competitive to other existing palmprint identification methods.
Year
Venue
Keywords
2016
2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
Palmprint identification, SIFT descriptors, Sparse representation, Fusion information
Field
DocType
ISSN
Scale-invariant feature transform,Computer vision,Pattern recognition,Computer science,Sparse approximation,Support vector machine,Feature extraction,Probability distribution,Artificial intelligence,Invariant (mathematics),Biometrics,Classifier (linguistics)
Conference
1062-922X
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Nesrine Charfi1101.49
Hanêne Trichili2364.72
Mohamed Adel Alimi31947217.16
Basel Solaiman412735.05