An Evaluation of Image Sampling and Compression for Human Iris Recognition

Rakshit, S.; Monro, D.M.

doi:10.1109/tifs.2007.902401

Cited by 58 publications

(25 citation statements)

References 37 publications

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“…Biometrics-based authentication systems are security technologies, which use human characteristics for personal identification. 1,2 These are increasingly replacing conventional systems for access control, identity management, and financial transactions. Among the many physiological and behavioural characteristics, such as signatures, used to identify individuals, iris recognition is considered one of the most reliable forms of automatic human identity verification.…”

Section: Introductionmentioning

confidence: 99%

Effect of cataract surgery and pupil dilation on iris pattern recognition for personal authentication

Dhir¹,

Habib²,

Monro

et al. 2009

Eye

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Purpose The purpose of this study was to investigate the effect of cataract surgery and pupil dilation on iris pattern recognition for personal authentication. Methods Prospective non-comparative cohort study. Images of 15 subjects were captured before (enrolment), and 5, 10, and 15 min after instillation of mydriatics before routine cataract surgery. After cataract surgery, images were captured 2 weeks thereafter. Enrolled and test images (after pupillary dilation and after cataract surgery) were segmented to extract the iris. This was then unwrapped onto a rectangular format for normalization and a novel method using the Discrete Cosine Transform was applied to encode the image into binary bits. The numerical difference between two iris codes (Hamming distance, HD) was calculated. The HD between identification and enrolment codes was used as a score and was compared with a confidence threshold for specific equipment, giving a match or non-match result. The Correct Recognition Rate (CRR) and Equal Error Rates (EERs) were calculated to analyse overall system performance. Results After cataract surgery, perfect identification and verification was achieved, with zero false acceptance rate, zero false rejection rate, and zero EER. After pupillary dilation, non-elastic deformation occurs and a CRR of 86.67% and EER of 9.33% were obtained. Conclusions Conventional circle-based localization methods are inadequate. Matching reliability decreases considerably with increase in pupillary dilation. Cataract surgery has no effect on iris pattern recognition, whereas pupil dilation may be used to defeat an iris-based authentication system.

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Section: Introductionmentioning

confidence: 99%

Effect of cataract surgery and pupil dilation on iris pattern recognition for personal authentication

Dhir¹,

Habib²,

Monro

et al. 2009

Eye

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“…A watershed event in fingerprint technology occurred in 1993 when the FBI adopted the Wavelet Scalar Quantization (WSQ) protocol [9] to compress vast libraries of fingerprint photograph cards that were digitised to 500 dpi, previously stored in acres of filing cabinets, to achieve compression ratios of typically 10:1 or 15:1. In the relatively new field of iris recognition [10,11], a pioneering study of iris compressibility was undertaken by Rakshit and Monro [12], showing unimpaired recognition performance for iris data extracted in polar format into data structures of 20,000 bytes (or 0.5 bpp). In this report we document three compression schemes that retain rectilinear image formats but achieve severe compression to as little as 2,000 bytes while still allowing very good recognition performance on the difficult NIST [13] ICE-1 publicly available iris image database.…”

Section: Introductionmentioning

confidence: 99%

Effect of Severe Image Compression on Iris Recognition Performance

Daugman

Downing

2008

IEEE Trans.Inform.Forensic Secur.

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We investigate three schemes for severe compression of iris images, in order to assess what their impact would be on recognition performance of the algorithms deployed today for identifying persons by this biometric feature. Currently, standard iris images are 600 times larger than the IrisCode templates computed from them for database storage and search; but it is administratively desired that iris data should be stored, transmitted, and embedded in media in the form of images rather than as templates computed with proprietary algorithms. To reconcile that goal with its implications for bandwidth and storage, we present schemes that combine region-of-interest isolation with JPEG and JPEG2000 compression at severe levels, and we test them using a publicly available government database of iris images. We show that it is possible to compress iris images to as little as 2 KB with minimal impact on recognition performance. Only some 2% to 3% of the bits in the IrisCode templates are changed by such severe image compression. Standard performance metrics such as error trade-off curves document very good recognition performance despite this reduction in data size by a net factor of 150, approaching a convergence of image data size and template size.

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“…To design and implement robust systems capable of mass deployment, one needs to address key issues, such as human factors, environmental conditions, system interoperability, and image standard [2].The iris, the colored portion of the eye surrounding the pupil, contains unique patterns which are prominent under nearinfrared illumination. These patterns remain stable from a very young age, barring trauma or disease, allowing accurate identification with a very high level of confidence.…”

Section: Introductionmentioning

confidence: 99%

Iris Compression and Recognition using Spherical Geometry Image

Ramadan¹

2015

ijarai

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Abstract-this research is considered to be a research to attract attention to the 3D iris compression to store the database of the iris. Actually, the 3D iris database cannot be found and in trying to solve this problem 2D iris database images are converted to 3D images just to implement the compression techniques used in 3D domain to test it and give an approximation results or to focus on this new direction in research. In this research a fully automated 3D iris compression and recognition system is presented. We use spherical based wavelet coefficients for efficient representation of the 3D iris. The spherical wavelet transformation is used to decompose the iris image into multi-resolution sub images. The representation of features based on spherical wavelet parameterization of the iris image was proposed for the 3D iris compression system. To evaluate the performance of the proposed approach, experiments were performed on the CASIA Iris database. Experimental results show that the spherical wavelet coefficients yield excellent compression capabilities with minimal set of features. Haar wavelet coefficients extracted from the iris image was found to generate good recognition results.

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An Evaluation of Image Sampling and Compression for Human Iris Recognition

Cited by 58 publications

References 37 publications

Effect of cataract surgery and pupil dilation on iris pattern recognition for personal authentication

Effect of cataract surgery and pupil dilation on iris pattern recognition for personal authentication

Effect of Severe Image Compression on Iris Recognition Performance

Iris Compression and Recognition using Spherical Geometry Image

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