Designing palmprint based recognition system using local structure tensor and force field transformation for human identification

Tiwari, Kamlesh; Arya, Devendra Kumar; Badrinath, G. S.; Gupta, Phalguni

doi:10.1016/j.neucom.2011.12.065

Cited by 28 publications

(8 citation statements)

References 22 publications

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“…If the Euclidean distance between pair of feature vector is less than or equal to T, then they are considered to belong to the same individual else they are considered to belong to different individuals. In the verification experiment equal error rate(ERR) [13][14][15] is adopted to evaluate the performance of biometric systems. ERR is the crossing point between false acceptance rate (FAR) and false rejection rate(FRR).…”

Section: Resultsmentioning

confidence: 99%

Extraction of Region of Interest (ROI) for Palm Print and Inner Knuckle Print

Anitha¹,

Rao²

2015

IJCA

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This paper proposes an novel approach to extract the Region of interest (ROI) for palm print and inner knuckle print(IKP) from hand images captured from a digital camera. An new algorithm to detect candidate key points on hand region is described. Using the candidate key points a novel approach to locate the ROI of palm print and inner knuckle print is proposed. The proposed approach is evaluated using the database collected at our institute. The results obtained are promising and confirm the usefulness of proposed ROI extraction approach for developing hand based biometric recognition systems.

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Section: Resultsmentioning

confidence: 99%

Extraction of Region of Interest (ROI) for Palm Print and Inner Knuckle Print

Anitha¹,

Rao²

2015

IJCA

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“…[4] modeled a palmprint based recognition system which uses texture and dominant orientation pixels as features. [5] identified a palmprint recognition method which uses blanket dimension for extracting image texture information.…”

Section: Literature Reviewmentioning

confidence: 99%

PSO Watermarking Model for Multimodal Biometric System

Nair¹,

Aruna²

2014

IJCA

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Multimodal Biometric Watermarking System using multiple sources of information for establishing the individuality has been widely recognized, computational models for multimodal biometrics recognition have only recently got attention. In this paper multimodal biometric images such as fingerprint, palmprint, and iris are extracted individually and are fused together using Average, Minimum and Maximum fusion mechanism. The fused template is then watermarked using the PSO watermarking system. The biometric features used here are fingerprint, iris and palmprint. The image quality is measured by using various metrics such as Peak Signal Noise ratio(PSNR), Normalized Absolute Error(NAE) and Normalized Cross Correlation(NCC). CASIA database is chosen for the biometric images. All the images are 8 bit graylevel JPEG image with the resolution of 320*280.

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“…There exists personal recognition systems in literature which are based on single or a combination of biometric traits. Some of the well known biometric traits includes face [33,38], fingerprint [18,46,51,50], palmprint [3,49,48], ear [44], iris [40], knuckleprint [39,4,41] etc. Any biometric system consists of four major phases; viz.…”

Section: Introductionmentioning

confidence: 99%

Biometrics based observer free transferable E-cash

Tiwari

Gupta

2014

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

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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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Designing palmprint based recognition system using local structure tensor and force field transformation for human identification

Cited by 28 publications

References 22 publications

Extraction of Region of Interest (ROI) for Palm Print and Inner Knuckle Print

Extraction of Region of Interest (ROI) for Palm Print and Inner Knuckle Print

PSO Watermarking Model for Multimodal Biometric System

Biometrics based observer free transferable E-cash

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