Paper Info
Title
Bimodal biometric system based on SIFT descriptors of hand images
Abstract
Hand shape biometry is among the most popular biometrics employed to characterize a person in forensic applications, due to its simplicity of use and acceptance of individuals. However, this modality presents weaknesses which may make system inaccurate. In fact, people from the same family or twins may have related hand features. Therefore, the performance of the hand verification process depends highly on the hand descriptors. In this paper, we propose a new approach for personal verification combining hand shape and palmprint features extracted using the Scale Invariant Feature Transform (SIFT). This transform was improved its high distinction and efficiency in many applications especially in object recognition and video tracking. Our experiments on IITD hand database demonstrate promising results by fusing at matching level score the hand shape and palmprint modalities. These results are comparable with similar bimodal identification methods.
Year
DOI
Venue
2014
10.1109/SMC.2014.6974586
Systems, Man and Cybernetics
Keywords
DocType
ISSN
digital forensics,feature extraction,image matching,palmprint recognition,shape recognition,transforms,IITD hand database,SIFT descriptors,bimodal biometric system,bimodal identification methods,forensic applications,hand descriptors,hand images,hand shape biometry,hand shape modalities,hand verification process,object recognition,palmprint feature extraction,palmprint modalities,personal verification,scale invariant feature transform,video tracking,Hand Biometrics,Scale Invariant Feature Transform,fusion information,hand shape,palmprint verification
Conference
1062-922X
Citations 
PageRank 
References 
5
0.44
17
Authors
4
Name
Order
Citations
PageRank
Nesrine Charfi1101.49
Hanêne Trichili2364.72
Mohamed Adel Alimi31947217.16
Basel Solaiman412735.05