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Iris Recognition Using Improved Xor-Sum Code

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Iris Recognition Using Improved Xor-Sum Code. / Bala, N.; Vyas, R.; Gupta, R. et al.
Security and Privacy: Select Proceedings of ICSP 2020. ed. / Pantelimon Stănică; Sugata Gangopadhyay; Sumit Kumar Debnath. Singapore: Springer, 2021. p. 107-117 (Lecture Notes in Electrical Engineering; Vol. 744).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Bala, N, Vyas, R, Gupta, R & Kumar, A 2021, Iris Recognition Using Improved Xor-Sum Code. in P Stănică, S Gangopadhyay & SK Debnath (eds), Security and Privacy: Select Proceedings of ICSP 2020. Lecture Notes in Electrical Engineering, vol. 744, Springer, Singapore, pp. 107-117. https://doi.org/10.1007/978-981-33-6781-4_9

APA

Bala, N., Vyas, R., Gupta, R., & Kumar, A. (2021). Iris Recognition Using Improved Xor-Sum Code. In P. Stănică, S. Gangopadhyay, & S. K. Debnath (Eds.), Security and Privacy: Select Proceedings of ICSP 2020 (pp. 107-117). (Lecture Notes in Electrical Engineering; Vol. 744). Springer. https://doi.org/10.1007/978-981-33-6781-4_9

Vancouver

Bala N, Vyas R, Gupta R, Kumar A. Iris Recognition Using Improved Xor-Sum Code. In Stănică P, Gangopadhyay S, Debnath SK, editors, Security and Privacy: Select Proceedings of ICSP 2020. Singapore: Springer. 2021. p. 107-117. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-33-6781-4_9

Author

Bala, N. ; Vyas, R. ; Gupta, R. et al. / Iris Recognition Using Improved Xor-Sum Code. Security and Privacy: Select Proceedings of ICSP 2020. editor / Pantelimon Stănică ; Sugata Gangopadhyay ; Sumit Kumar Debnath. Singapore : Springer, 2021. pp. 107-117 (Lecture Notes in Electrical Engineering).

Bibtex

@inproceedings{354da684fa9242c7819f790e8a8a6037,
title = "Iris Recognition Using Improved Xor-Sum Code",
abstract = "Iris recognition has been among the most secure and reliable biometric traits, because of its permanent and unique features. Among the various essential modules of an iris recognition framework, feature extraction has been the most sought-for module, where numerous research works have been carried out to yield an effective representation of iris features. This paper is an attempt to propose an improved version of a famous feature descriptor, called Xor-sum code, to obtain an enhanced recognition accuracy. The proposed approach incorporates the curvature information into the conventional Gabor filter, to facilitate discriminative iris feature representation. A rigorous experimentation, with two challenging benchmark iris datasets, has been performed to approve the viability of suggested strategy. The approach proposed under this work is also generalized to work with both the near-infrared and visible wavelength images. ",
keywords = "Gabor filters, Infrared devices, Biometric traits, Curvature information, Feature descriptors, Iris recognition, Near Infrared, Recognition accuracy, Unique features, Visible wavelengths, Biometrics",
author = "N. Bala and R. Vyas and R. Gupta and A. Kumar",
year = "2021",
month = apr,
day = "2",
doi = "10.1007/978-981-33-6781-4_9",
language = "English",
isbn = "9789813367807 ",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer",
pages = "107--117",
editor = "Pantelimon St{\u a}nic{\u a} and Sugata Gangopadhyay and Debnath, {Sumit Kumar}",
booktitle = "Security and Privacy",

}

RIS

TY - GEN

T1 - Iris Recognition Using Improved Xor-Sum Code

AU - Bala, N.

AU - Vyas, R.

AU - Gupta, R.

AU - Kumar, A.

PY - 2021/4/2

Y1 - 2021/4/2

N2 - Iris recognition has been among the most secure and reliable biometric traits, because of its permanent and unique features. Among the various essential modules of an iris recognition framework, feature extraction has been the most sought-for module, where numerous research works have been carried out to yield an effective representation of iris features. This paper is an attempt to propose an improved version of a famous feature descriptor, called Xor-sum code, to obtain an enhanced recognition accuracy. The proposed approach incorporates the curvature information into the conventional Gabor filter, to facilitate discriminative iris feature representation. A rigorous experimentation, with two challenging benchmark iris datasets, has been performed to approve the viability of suggested strategy. The approach proposed under this work is also generalized to work with both the near-infrared and visible wavelength images.

AB - Iris recognition has been among the most secure and reliable biometric traits, because of its permanent and unique features. Among the various essential modules of an iris recognition framework, feature extraction has been the most sought-for module, where numerous research works have been carried out to yield an effective representation of iris features. This paper is an attempt to propose an improved version of a famous feature descriptor, called Xor-sum code, to obtain an enhanced recognition accuracy. The proposed approach incorporates the curvature information into the conventional Gabor filter, to facilitate discriminative iris feature representation. A rigorous experimentation, with two challenging benchmark iris datasets, has been performed to approve the viability of suggested strategy. The approach proposed under this work is also generalized to work with both the near-infrared and visible wavelength images.

KW - Gabor filters

KW - Infrared devices

KW - Biometric traits

KW - Curvature information

KW - Feature descriptors

KW - Iris recognition

KW - Near Infrared

KW - Recognition accuracy

KW - Unique features

KW - Visible wavelengths

KW - Biometrics

U2 - 10.1007/978-981-33-6781-4_9

DO - 10.1007/978-981-33-6781-4_9

M3 - Conference contribution/Paper

SN - 9789813367807

SN - 9789813367838

T3 - Lecture Notes in Electrical Engineering

SP - 107

EP - 117

BT - Security and Privacy

A2 - Stănică, Pantelimon

A2 - Gangopadhyay, Sugata

A2 - Debnath, Sumit Kumar

PB - Springer

CY - Singapore

ER -