Segmentation of Slap Fingerprint Images

Proceedings of the 2nd ACM Workshop on Information Hiding and Multimedia Security

2014

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This paper proposes a transaction strategy to implement transferable E-cash. It does not involve any third party observer at the time of transaction and possesses strong anonymity property. It uses biometric features of the legitimate holder of e-cash to progress the transaction. It works on the transfer of coin ownership and is built around the restrictive blinding and biometric digital signature scheme. Its mathematical model utilizes the hardness of discrete log problem and representation problem in groups. It guarantees anonymity and unlinkability for a genuine user and non repudiation to a fraudulent one.

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Section: Introductionmentioning

confidence: 99%

Biometrics based observer free transferable E-cash

Proceedings of the 2nd ACM Workshop on Information Hiding and Multimedia Security

2014

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“…Error rates are utilized in [7]. Biometrics systems such as palmprint [22], [23], [5], fingerprint [25], [28], [20], knuckle [4], vein pattern [21] and their applications [24], [30] are more apt to adaptive fusion. There is a need for a sophisticated fusion scheme which is adaptive to the underline statistical properties of a biometric system such as error rate and accuracy for their normalization and fusion.…”

Section: Introductionmentioning

confidence: 99%

TARC: A novel score fusion scheme for multimodal biometric systems

Nigam

2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)

2014

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This paper proposes a score level fusion scheme for a multimodal biometric system. Accuracy and reliability of a system are improved by utilizing more than one samples. Every matching of a biometric sample with its corresponding biometric sample in the database produces a matching score. There multiple scores from different biometric samples are fused for further utilization. It proposes an efficient threshold alignment and range compression scheme for score normalization. It uses statistical properties of biometric score distribution. The proposed scheme has been tested over a multimodal database which is constructed by using three publicly available database viz. FVC2006-DB2-A of fingerprint, CASIA-V4-Lamp of iris and PolyU of palmprint. Experimental results have shown the significant performance boost.978-1-4799-4533-7/14/$31.00 ©2014 IEEE

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No-Reference Fingerprint Image Quality Assessment

Intelligent Computing Methodologies

2014