A review of biometric technology along with trends and prospects

Unar, Jawed Akhtar; Seng, Woo Chaw; Abbasi, Almas

doi:10.1016/j.patcog.2014.01.016

Cited by 343 publications

(202 citation statements)

References 223 publications

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“…Iris patterns can also be used in airport check-in, criminal identification, access control, computer logins, e-commerce, welfare disbursements, missing children identification, passports, time and attendance monitoring systems etc. 4 Iris pattern acquisition is one of the important attributes Iris is an eye muscle that regulates the size of the pupil to control the amount of light entering the eye and its coloration pattern depends upon the amount of melanin pigment present in it [9][10] . Iris is a multi-layered structure lying in front of the crystalline lens and the ciliary body which separates the anterior and posterior chambers of eye.…”

Section: Iris Recognition As a Forensic Toolmentioning

confidence: 99%

“…It is present in the form of a truncated cone possessing unique and random features like freckle, coronas, crypts, furrows, pigments, blood vessels etc 9,11,12 (Figure 1). Such randomly distributed and irregularly shaped micro-structures of human iris (i.e., minutiae) start developing early intra-uterine life, though it fully develops within a month after birth 5,[3][4][5][6][7][8][9][10][11][12][13][14][15] . Iris recognition is an accurate, fast, easy to use, non-intrusive and inimitable or unforgable mean of authentication and identification that can replace current methods of passwords, token cards, pin numbers, OTPs etc.…”

Section: Iris Recognition As a Forensic Toolmentioning

confidence: 99%

“…organizations/establishments. Rapidly growing incidents of criminal Orlando shootings and Brussels airport explosions), have necessitated the introduction of some more advanced security and surveillance systems to replace the traditional and obsolete methods 4 . The uniqueness, permanence, measurability, performance, acceptability, universality, and low circumvention are the important characteristics of a biometric trait to make it suitable for forensic identifications 5 , and Iris pattern recognition is one of forensic modality having all these characteristics which can work even in nonideal situations 3 .…”

mentioning

confidence: 99%

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Iris Patterns As A Biometric Tool For Forensic Identifications: A Review

Sehrawat¹,

Sankhyan²

2016

BJFS

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Biometric identificationAbsolute personal recognition is effectively required in many applications like secure access to buildings, sensitive premises (i.e., nuclear reactors, defense establishments) laptops, cellular phones, computer systems, ATMs etc. Biometric recognition or, simply, biometrics is the automatic recognition of individuals based on their physiological and/or behavioral characteristics like fingerprints, face, hand geometry, retina, ear, iris, speech, voice, signatures, handwriting, gait etc 1 . A biometric system first captures the data, removes the redundant features, constructs a template and compares it with other templates from a database in order to verify or identify an individual. Diversification of crime, criminal and criminality has invited the focussed

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Section: Iris Recognition As a Forensic Toolmentioning

confidence: 99%

Section: Iris Recognition As a Forensic Toolmentioning

confidence: 99%

mentioning

confidence: 99%

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Iris Patterns As A Biometric Tool For Forensic Identifications: A Review

Sehrawat¹,

Sankhyan²

2016

BJFS

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“…With advances in technology, biometric systems have emerged to identify individuals using biological features. Examples of biological features as biometric traits include face, fingerprint, iris, retina, hand geometry, voice, signature, gait, heart signal and so on [5], [13], [21], [30]. While considering facial biometric, face recognition aims for automatically identifying individuals from their digital images or video frames using physiological features.…”

Section: Introductionmentioning

confidence: 99%

Changes in Facial Expression as Biometric: A Database and Benchmarks of Identification

Haamer

Kulkarni

Imanpour

et al. 2018

2018 13th IEEE International Conference on Automatic Face &Amp; Gesture Recognition (FG 2018)

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Abstract-Facial dynamics can be considered as unique signatures for discrimination between people. These have started to become important topic since many devices have the possibility of unlocking using face recognition or verification. In this work, we evaluate the efficacy of the transition frames of video in emotion as compared to the peak emotion frames for identification. For experiments with transition frames we extract features from each frame of the video from a fine-tuned VGG-Face Convolutional Neural Network (CNN) and geometric features from facial landmark points. To model the temporal context of the transition frames we train a Long-Short Term Memory (LSTM) on the geometric and the CNN features. Furthermore, we employ two fusion strategies: first, an early fusion, in which the geometric and the CNN features are stacked and fed to the LSTM. Second, a late fusion, in which the prediction of the LSTMs, trained independently on the two features, are stacked and used with a Support Vector Machine (SVM). Experimental results show that the late fusion strategy gives the best results and the transition frames give better identification results as compared to the peak emotion frames.

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“…Fingerprints have provided an impeccable means of user authentication and personal identification for a long time, possibly dating back to the 19th century, when the records of fingerprint details of criminals in Argentina were released [20]. It has long since been adopted not just for law enforcement purposes (forensics and police) but also for commercial purposes like financial transactions and most recently, it is used as an authentication method in mobile devices and computers.…”

Section: Introductionmentioning

confidence: 99%

Identification of Fingerprints using Circular String Approximation for Mobile Devices

Ajala

Iliopoulos

Khan

2017

Annals of Computer Science and Information Systems

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Abstract-Lately, Biometrics has employed the use of fingerprints to identify individuals. Out of the commonly used techniques, fingerprint authentication till date remains the most reliable. The bulk of research that has focused on fingerprint authentication, has however, neglected the issues that arise with fingerprints resulting to incorrect orientation identification. This is because it is assumed and often times wrongly, that the direction of the fingerprint will align with the stored fingerprint image. This singular issue poses tension in fingerprint matching, which only a negligible number of techniques have considered. As computers and mobile devices adopt fingerprint recognition as a way to authenticate the user, this apparent tension gains more popularity, becoming an integral research area which must be addressed.Responding to this issue, this report proposes a novel pattern matching technique that caters for orientation differences in fingerprints, by implementing a pre-matching stage called the orientation identification stage and then match the fingerprint image with stored images using algorithms for approximate circular string matching. This fingerprint string information is now matched against a database of stored images using approximate string matching techniques.

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A review of biometric technology along with trends and prospects

Cited by 343 publications

References 223 publications

Iris Patterns As A Biometric Tool For Forensic Identifications: A Review

Iris Patterns As A Biometric Tool For Forensic Identifications: A Review

Changes in Facial Expression as Biometric: A Database and Benchmarks of Identification

Identification of Fingerprints using Circular String Approximation for Mobile Devices

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