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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2009年第6期31卷 964-973页

作者： Hollingsworth, Karen P. Bowyer, Kevin W. Flynn, Patrick J. Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

iris biometric systems apply filters to iris images to extract information about iris texture. Daugman's approach maps the filter output to a binary iris code. The fractional Hamming distance between two iris codes is computed and decisions about the identity of a person are based on the computed distance. The fractional Hamming distance weights all bits in an iris code equally. However, not all of the bits in an iris code are equally useful. Our research is the first to present experiments documenting that some bits are more consistent than others. Different regions of the iris are compared to evaluate their relative consistency and, contrary to some previous research, we find that the middle bands of the iris are more consistent than the inner bands. The inconsistent-bit phenomenon is evident across genders and different filter types. Possible causes of inconsistencies, such as segmentation, alignment issues, and different filters, are investigated. The inconsistencies are largely due to the coarse quantization of the phase response. Masking iris code bits corresponding to complex filter responses near the axes of the complex plane improves the separation between the match and nonmatch Hamming distance distributions.

关键词： iris biometrics iris code texture filter false reject rate

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TRACKING AND TRACEABILITY SYSTEM USING LIVESTOCK iris code IN MEAT SUPPLY CHAIN

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2011年第5A期7卷 2201-2212页

作者： Zhao, Lindu Sun, Shengnan Wang, Xiaoqiang Southeast Univ Inst Syst Engn Nanjing 210096 Peoples R China

As the global development of food industry and trade, emergent event on food safety shows rapid expansion and spreading, such as hand-foot-and-mouth disease and bovine spongiform encephalopathy (BSE or mad cow disease). Food safety concerns have put tracking and tracing at the center point of discussion. However, in food Commodities, the establishment of tracking and tracing capability meets many barriers that have prevented their broad use. The prominent problem is to establish a feasible identification (ID) system capable of quick tracking animals from birth to slaughter, and tracing meat from consumer to farm. This paper introduces a tracking and traceability system for meat supply chain, using livestock iris code. In the tracking module, iris code is used to mark large animal, such as pig, cattle and sheep, which are the main source of meat. And in the traceability module, two-dimension iris code, generated from the iris code, is printed in product package to help consumers to trace the product from supermarket to plant. This paper takes cattle as an experimental object, and generates iris code by using suitable algorithms.

关键词： Tracking and traceability iris code Meat supply chain Two-dimension iris code Food safety

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Using Fusion of iris code and Periocular Biometric for Matching Visible Spectrum iris Images Captured by Smart Phone Cameras 23

Using Fusion of Iris Code and Periocular Biometric for Match...

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23rd International Conference on Pattern Recognition (ICPR)

作者： Ahmed, Nasir Udin Cvetkovic, Slobodan Siddiqi, Erfanul Hoque Nikiforov, Andrey Nikiforov, Ilia TigerIT Dhaka Bangladesh

ISBN: (纸本)9781509048472

This paper describes iris biometric matching performed using the iris pictures captured by the standard visible spectrum smart phone cameras from the MICHE II database. Our method uses a combination of a popular iris code approach and a periocular biometric based on the Multi-Block Transitional Local Binary Patterns. The authentication scores are calculated separately, and the results are combined to improve the system performance.

关键词： noisy iris recognition visible spectrum iris code local binary pattern multimodal biometrics score level fusion

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Part based bit error analysis of iris codes

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PATTERN RECOGNITION 2016年 60卷 306-317页

作者： Tomeo-Reyes, I. Chandran, V. Queensland Univ Technol 2 George St Brisbane Qld Australia

In order to effectively use iris patterns in biometric recognition, there is value in knowing how bit errors in iris codes are distributed. In this work, the iris is considered in a part-based framework as rings and sectors. A mean normalised bit error is defined as the bit error averaged over the entire part and over an ensemble of images. The distribution of this error for genuine comparisons is investigated as a function of radius (ring) and angle (sector) for a range of factors more comprehensively than previous studies of consistency of iris codes. Two iris recognition systems and three data sets are used. The effect of residual segmentation errors after automated segmentation is checked, and masks are manually refined to obtain segmentation error free data for further investigation. The effect of factors such as capture sensor, re sampling, input iris image resolution, filter type and encoding scheme, and changes in pupil size is systematically investigated. Results confirm the finding in previous works that the pupillary and limbic boundaries are more error-prone than the middle region of the iris. This study further confirms that this V-shaped radial trend is not significantly disturbed by any of the above factors other than pupil size changes. Both pupil dilation and constriction result in increased bit errors which no longer show a dip in the middle region of the iris. The distribution of errors as a function of angle is approximately uniform regardless of the factor investigated but shows a small decrease towards the sectors near the eye corners. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： iris recognition iris code Consistent bits Error distribution

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Optimal Generation of iris codes for iris Recognition

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2017年第1期12卷 157-171页

作者： Hu, Yang Sirlantzis, Konstantinos Howells, Gareth Univ Kent Sch Engn & Digital Arts Canterbury CT2 7NT Kent England

The calculation of binary iris codes from feature values (e.g., the result of Gabor transform) is a key step in iris recognition systems. Traditional binarization method based on the sign of feature values has achieved very promising performance. However, currently, little research focuses on a deeper insight into this binarization method to produce iris codes. In this paper, we illustrate the iris code calculation from the perspective of optimization. We demonstrate that the traditional iris code is the solution of an optimization problem, which minimizes the distance between the feature values and the iris codes. Furthermore, we show that more effective iris codes can be obtained by adding terms to the objective function of this optimization problem. We investigate two additional objective terms. The first objective term exploits the spatial relationships of the bits in different positions of an iris code. The second objective term mitigates the influence of less reliable bits in iris codes. The two objective terms can be applied to the optimization problem individually, or in a combined scheme. We conduct experiments on four benchmark datasets with varying image quality. The experimental results demonstrate that the iris code produced by solving the optimization problem with the two additional objective terms achieves a generally improved performance in comparison to the traditional iris code calculated by binarizing feature values based on their signs.

关键词： iris recognition iris code spatial relationship feature reliability

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Proposal of a transformation method for iris codes in iris scanning verification

Proposal of a transformation method for iris codes in iris s...

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Symposium on Cryptography and Information Security

作者： Ota, H Kiyomoto, S Tanaka, T KDDI R&D Labs Inc Kamifukuoka Saitama 3568502 Japan

In this paper, we propose a transformation function for a user's raw iris data, an "iris code" in iris scanning verification on the server, since the iris code requires to be hidden from even a server administrator. We then show that the user can be properly authenticated on the server. even though the iris code is transformed by the proposed function. The reason is that the function has a characteristic, "The (normalized) Hamming distances between the enrolled iris codes and the verified iris codes are conserved before and after the computation of the function," that is. the normalized Hamming distance in this scheme is equal to that in the existing scheme. We also show that the transformed iris code is sufficiently secure to hide the original iris code, even if a stronger attack model is supposed than the previously described model. That can be explained from the following two reasons. One reason is that nonlinear function, which consists of the three-dimensional rotation about the x-axis and the y-axis with the iris code lengthened bit by bit, and the cyclic shift. does not enable an attacker to conjecture the iris code. The other reason is that the success probabilities for the exhaustive search attack concerning the iris code in the supposed attack models are lower than those of the previously proposed methods and are negligible.

关键词： iris scanning verification iris code transformation function hiding exhaustive search attack

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Optimization of iris codes for Improved Recognition

Optimization of Iris Codes for Improved Recognition

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27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Mahadeo, Nitin K. Paplinski, Andrew P. Ray, Sid Monash Univ Clayton Sch Informat Technol Clayton Vic 3800 Australia

ISBN: (纸本)9781479943098

The texture of the iris is commonly represented as an iris code in iris recognition systems. While several approaches have been presented for generating iris codes, relatively few comparison techniques have been proposed. In this paper, we take advantage of the availability of several frames from an iris video to create a single optimized iris code. This is achieved by performing both row-wise and column-wise optimization of iris codes. Inconsistent bits are accurately detected and masked in the final iris code. Our experiments demonstrate that by exploiting variations within the comparison scores of different rows and columns of N frames, we are able to derive the number of consistent bits in the final iris code thereby resulting in significant improvement in recognition performance. We compare our algorithm with well-known methods, namely, Fragile bit masking, Signal fusion and, two Score Fusion techniques. Experimental results on a dataset of 986 iris videos show that the proposed method is encouraging and comparable to the best algorithms in the current literature. To our knowledge, this is the first work that makes use of the best rows and columns from different frames in an iris video to improve performance.

关键词： Biometrics iris code iris recognition Matching Performance

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Combining iris and periocular biometric for matching visible spectrum eye images

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PATTERN RECOGNITION LETTERS 2017年第May 1期91卷 11-16页

作者： Ahmed, Nasir Udin Cvetkovic, Slobodan Siddiqi, Erfanul Hoque Nikiforov, Andrey Nikiforov, Ilia Tiger IT House 21Rd 28Block K Dhaka 1213 Bangladesh

This paper describes biometric matching of eye images captured by the visible spectrum smart phone cameras from the MICHE II database. The matching is performed by calculating matching scores for iris codes and periocular biometric based on the Multi-Block Transitional Local Binary Patterns. The authentication scores are calculated separately, and the results are fused to improve the system performance. Score fusion significantly improves error statistics compared to individual iris and periocular matching. For example, equal error rate is about two times lower for fused scores compared to the separate iris and periocular matching. Our matching algorithm ranked first in MICHE II competition. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Noisy iris recognition Visible spectrum iris code Local binary pattern Multimodal biometrics Score level fusion

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iris Recognition Using Signal-Level Fusion of Frames From Video

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2009年第4期4卷 837-848页

作者： Hollingsworth, Karen Peters, Tanya Bowyer, Kevin W. Flynn, Patrick J. Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

We take advantage of the temporal continuity in an iris video to improve matching performance using signal-level fusion. From multiple frames of a frontal iris video, we create a single average image. For comparison, we reimplement three score-level fusion methods (Ma et al., Krichen et al., and Schmid et al.). We find that our signal-level fusion of images performs better than Ma's or Krichen's score-level fusion methods of Hamming distance scores. Our signal-level fusion performs comparably to Schmid's log-likelihood method of score-level fusion, and our method achieves this performance using less computation time. We compare our signal fusion method with another new method: a multigallery, multiprobe method involving score-level fusion of Hamming distances. The multigallery, multiprobe score fusion has slightly better recognition performance, while the signal fusion has significant advantages in memory and computation requirements. No published prior work has shown any advantage of the use of video over still images in iris biometrics.

关键词： Image averaging iris biometrics iris code iris video noise reduction score-level fusion signal-level fusion

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A new accurate noise-removing approach for non-cooperative iris recognition

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SIGNAL IMAGE AND VIDEO PROCESSING 2014年第1期8卷 1-10页

作者： Ghodrati, Hamed Dehghani, Mohammad Javad Danyali, Habibolah Shiraz Univ Technol Dept Telecommun Engn Shiraz Iran

The applications of biometric technology for automated personal identification become ubiquitous. iris recognition is well known for high accuracy and reliability among the biometric traits. This paper presents an efficient noise-removing approach for non-cooperative iris recognition systems. Proposed method removed the noise factors including eyelids, eyelashes, reflections, out of framework, pupil and sclera. The novelty is to detect eyelashes and reflections through finding appropriate thresholds using a procedure called statistical decision making. The eyelids are detected using parabolic Hough transform in normalized iris image to increase computational speed. In addition, a coarse-to-fine strategy for accurate and fast iris localization is proposed. The Gabor-wavelet and a novel encoding strategy proposed in our previous work are also used here to generate the iris codes. We elaborate the principle of mask code generation to assign noisy bits in an iris code to exclude them in matching step. Experimental results on CASIA-irisV3-Interval database show superiority of the proposed scheme among other state-of-the-art methods available in the literature.

关键词： iris segmentation Noise-removing Statistical decision making iris code Mask code Hough transform

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