A novel algorithm for secure Internet Banking with finger print recognition

Priya, R.; V.Tamilselvi,; Rameshkumar, G. P.

doi:10.1109/embeddedsys.2014.6953099

Cited by 10 publications

(7 citation statements)

References 2 publications

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“…These systems usually rely on "local discontinuities in the ridge flow pattern" called minutiae. According to the empirical study, two individuals will not have more than seven common minutiae [4,5]. The set of minutiae are restricted into two types Ridge endings and Ridge bifurcations.…”

Section: Minutiae Based Systems 2 Patter (Image) Based Systemsmentioning

confidence: 99%

Overview of Biometric Fingerprint Identification

Jain¹,

Khurana²

2018

IJTSRD

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Fingerprint identification of a person is widely used in all over the world, as there are no two fingerprints like. Authentication and validation of an individual is done with the help of various factors like signature, user-ids and passwords, palm, fingerprint, face, voice, heartbeat , iris, etc. The fingerprint technique is advantageous for such recognition as compare other techniques. This paper is a brief review in the field of fingerprint identification. The aim of this paper is to review various latest minutiae based, correlation based and other global, local methods for fingerprint matching and status of succe concurrent methods.

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Section: Minutiae Based Systems 2 Patter (Image) Based Systemsmentioning

confidence: 99%

Overview of Biometric Fingerprint Identification

Jain¹,

Khurana²

2018

IJTSRD

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“…Fingerprint identification [1]- [7] is the most susceptible biometric method developed in the framework of dactyloscopy, discipline of criminal technique, which deals with the study of papillary lines (or papillae), formed in various forms on the cheeks and fingers, palms and feet.…”

Section: Introductionmentioning

confidence: 99%

Fingerprint Recognition under Missing Image Pixels Scenario

Brajovic

Tomovic

Radonjic

2019

2019 8th Mediterranean Conference on Embedded Computing (MECO)

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This work observed the problem of fingerprint image recognition in the case of missing pixels from the original image. The possibility of missing pixels recovery is tested by applying the Compressive Sensing approach. Namely, different percentage of missing pixels is observed and the image reconstruction is done by applying commonly used approach for sparse image reconstruction. The theory is verified by experiments, showing successful image reconstruction and later person identification even if less then 90% of the image pixels is missing.

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“…In investment fraud, al. [26] argued that hacking is problems in online banking. Besides another cybercrime activities malware [26].…”

Section: 3examples Of Criminal Bankingmentioning

confidence: 99%

“…[26] argued that hacking is problems in online banking. Besides another cybercrime activities malware [26]. Example of Phishing emails representing a bank where details in order to deceive personal be used in illegal activities [27].…”

Section: 3examples Of Criminal Bankingmentioning

confidence: 99%