Iris Recognition using Cumulative SUM based Change Analysis

Ko, Jong-Gook; Gil, Yeon-Hee; Yoo, Ji-Sang

doi:10.1109/ispacs.2006.364885

Cited by 17 publications

(7 citation statements)

References 8 publications

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“…Since, the algorithm of Ma is very similar to that of Masek (1-D wavelet transform is applied to ten 1-D intensity signals of length 512 at two subbands) obtained MSs turn out to be high. In contrast, if we match both textures with our implementation of the algorithm of Ko [3] which is based on a completely different feature extraction (changes in cumulative sums of grayscale pixel-blocks are observed) a MS of 45.73% is obtained. Based on 50 generated iris textures we have found that these observations hold in general as can be seen in Tab.…”

Section: Block Detectionmentioning

confidence: 99%

Attacking Iris Recognition: An Efficient Hill-Climbing Technique

Rathgeb

Uhl

2010

2010 20th International Conference on Pattern Recognition

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Section: Block Detectionmentioning

confidence: 99%

Attacking Iris Recognition: An Efficient Hill-Climbing Technique

Rathgeb

Uhl

2010

2010 20th International Conference on Pattern Recognition

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“…We evaluate its matching performance on iris trait by extracting binary feature vectors from a subset of CASIA V3 iris dataset [1] consisting of 100 individuals with 8 samples each. Iriscodes are extracted based on the scheme presented by Ko et al [12] and then binarized using a similar approach as Rathgeb et al's [18] to output a 2000 bit feature vector. The iris region is first segmented as described by Daugman et al [3].…”

Section: Methodsmentioning

confidence: 99%

One-Time Biometric Token based Authentication

Kulkarni

Namboodiri

2014

Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing

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Widely used online commerce systems require an user to submit his sole banking credentials or credit card details for availing desired services, thus involving high risks with untrusted service providers. Often used one-time password based systems provide additional transaction security, but are still incapable of differentiating between a genuine user trying to authenticate or an adversary with stolen credentials. This brings out a strong need for biometrics based onetime password systems. In this paper we propose a one-time biometric token based authentication protocol which works within the framework of current online transaction schemes allowing an user to carry out a financial transaction with a service provider which completes with an authorization from the bank. The proposed protocol is based on key-binding biometric cryptosystems and upholds the requirements of secure authentication, template protection and revocability while providing privacy to individual's biometrics and anonymity from the service provider. We demonstrate our system's security and performance using iris biometrics to authenticate individuals.

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“…Cumulative Sum Based Analysis Method [5] is used to extract features from iris images. It analyzes the grey values patterns in iris image and hence extracts iris features.…”

Section: Iris Feature Extraction and Encodingmentioning

confidence: 99%

Enhanced Iris Recognition System – an Integrated Approach to Person Identification

Kaur¹,

Girdhar²,

Kaur³

2010

IJCA

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This paper discusses about Enhanced iris recognition which is used to overcome some of the problem like to automate the recognition of the iris by reducing complexity and increasing algorithm speed. Various challenges are faced while working with the iris recognition system. Iris recognition systems make use of the uniqueness of the iris patterns to derive a unique mapping. Iris recognition, as a biometric method, outperforms others because of its high accuracy. Iris recognition also has the ability to handle very large populations at high speed. Mostly three stages are followed while working with iris system i.e. preprocessing, feature extraction and recognition stage. This paper presents an automated and novel iris recognition system where overall computational match speed is reduced (from iris preprocessing to the final stage of recognition) and hence makes system more reliable with accuracy of 99.38% and low FAR.

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Iris Recognition using Cumulative SUM based Change Analysis

Cited by 17 publications

References 8 publications

Attacking Iris Recognition: An Efficient Hill-Climbing Technique

Attacking Iris Recognition: An Efficient Hill-Climbing Technique

One-Time Biometric Token based Authentication

Enhanced Iris Recognition System – an Integrated Approach to Person Identification

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