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141
Ubiris: A noisy iris image database
- Tech. Rep
, 2005
"... Abstract. This paper presents a new iris database that contains images with noise. This is in contrast with the existing databases, that are noise free. UBIRIS is a tool for the development of robust iris recognition algorithms for biometric proposes. We present a detailed description of the many ch ..."
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Cited by 65 (10 self)
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Abstract. This paper presents a new iris database that contains images with noise. This is in contrast with the existing databases, that are noise free. UBIRIS is a tool for the development of robust iris recognition algorithms for biometric proposes. We present a detailed description of the many characteristics of UBIRIS and a comparison of several image segmentation approaches used in the current iris segmentation methods where it is evident their small tolerance to noisy images. 1
Experiments with an improved iris segmentation algorithm
- in: IEEE Workshop on Automatic Identification Advanced Technologies (AutoID), 2005
"... Iris is claimed to be one of the best biometrics. We have collected a large data set of iris images, intention-ally sampling a range of quality broader than that used by current commercial iris recognition systems. We have re-implemented the Daugman-like iris recognition algorithm developed by Masek ..."
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Cited by 44 (23 self)
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Iris is claimed to be one of the best biometrics. We have collected a large data set of iris images, intention-ally sampling a range of quality broader than that used by current commercial iris recognition systems. We have re-implemented the Daugman-like iris recognition algorithm developed by Masek. We have also developed and imple-mented an improved iris segmentation and eyelid detection stage of the algorithm, and experimentally verified the im-provement in recognition performance using the collected dataset. Compared to Masek’s original segmentation ap-proach, our improved segmentation algorithm leads to an increase of over 6 % in the rank-one recognition rate. 1.
Secure biometrics via syndromes
- in Allerton Conf
, 2005
"... We consider the secure biometric storage problem and develop a solution using syndrome codes. Specifically, biometrics such as fingerprints, irises, and faces are often used for authentication, access control, and encryption instead of passwords. While it is well known that passwords should never be ..."
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Cited by 25 (4 self)
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We consider the secure biometric storage problem and develop a solution using syndrome codes. Specifically, biometrics such as fingerprints, irises, and faces are often used for authentication, access control, and encryption instead of passwords. While it is well known that passwords should never be stored in the clear, current systems often store biometrics in the clear and are easily compromised. We describe the secure biometric storage problem by discussing the insecurities in current systems, the reasons why password hashing/encryption algorithms are unsuitable for biometrics, and propose a secure biometric storage framework based on syndrome codes and the Slepian-Wolf theorem. 1
Iris Segmentation Using Geodesic Active Contours
"... Abstract—The richness and apparent stability of the iris texture make it a robust biometric trait for personal authentication. The performance of an automated iris recognition system is affected by the accuracy of the segmentation process used to localize the iris structure. Most segmentation models ..."
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Cited by 24 (2 self)
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Abstract—The richness and apparent stability of the iris texture make it a robust biometric trait for personal authentication. The performance of an automated iris recognition system is affected by the accuracy of the segmentation process used to localize the iris structure. Most segmentation models in the literature assume that the pupillary, limbic, and eyelid boundaries are circular or elliptical in shape. Hence, they focus on determining model parameters that best fit these hypotheses. However, it is difficult to segment iris images acquired under nonideal conditions using such conic models. In this paper, we describe a novel iris segmentation scheme employing geodesic active contours (GACs) to extract the iris from the surrounding structures. Since active contours can 1) assume any shape and 2) segment multiple objects simultaneously, they mitigate some of the concerns associated with traditional iris segmentation models. The proposed scheme elicits the iris texture in an iterative fashion and is guided by both local and global properties of the image. The matching accuracy of an iris recognition system is observed to improve upon application of the proposed segmentation algorithm. Experimental results on the CASIA v3.0 and WVU nonideal iris databases indicate the efficacy of the proposed technique. Index Terms—Geodesic active contours (GACs), iriscodes, iris recognition, iris segmentation, level sets, snakes. Fig. 1. Block diagram of an iris recognition system.
Comparison and Combination of Iris Matchers for Reliable Personal Identification
"... The biometric identification approaches using iris images are receiving increasing attention in the literature. Several methods for the automated iris identification have been presented in the literature and those based on the phase encoding of texture information are suggested to be the most promis ..."
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Cited by 22 (1 self)
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The biometric identification approaches using iris images are receiving increasing attention in the literature. Several methods for the automated iris identification have been presented in the literature and those based on the phase encoding of texture information are suggested to be the most promising. However, there has not been any attempt to combine these phase preserving approaches to achieve further improvement in the performance. This paper presents a comparative study of the performance from the iris identification using log-Gabor, Haar wavelet, DCT and FFT based features. Our experimental results suggest that the performance from the Haar wavelet and log Gabor filter based phase encoding is the most promising among all the four approaches considered in this work. Therefore the combination of these two matchers is most promising, both in terms of performance and the computational complexity. Our experimental results from the all 411 users (CASIA v3) and 224 users (IITD v1) database illustrate significant improvement in the performance that is not possible with either of these approaches individually. 1.
Multispectral Iris Analysis: A Preliminary Study
"... This paper explores the possibility of using multispectral iris information to enhance the recognition performance of an iris biometric system. Commercial iris recognition systems typically sense the iridal reflection pertaining to the near-infrared (IR) range of the electromagnetic spectrum. This w ..."
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Cited by 19 (7 self)
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This paper explores the possibility of using multispectral iris information to enhance the recognition performance of an iris biometric system. Commercial iris recognition systems typically sense the iridal reflection pertaining to the near-infrared (IR) range of the electromagnetic spectrum. This work examines the iris information represented in the visible and IR portion of the spectrum. It is hypothesized that, based on the color of the eye, different components of the iris are highlighted at multiple wavelengths. To this end, an acquisition procedure for obtaining co-registered multispectral iris images associated with the IR, Red, Green and Blue wavelengths of the electromagnetic spectrum, is first discussed. The components of the iris that are revealed in multiple spectral channels/wavelengths based on the color of the eye are studied. An adaptive histogram equalization scheme is invoked to enhance the iris structure. The performance of iris recognition across multiple wavelengths is next evaluated. Experiments indicate the potential of
Performance evaluation of iris based recognition system implementing
- PCA and ICA techniques,” Proc. of the SPIE 2005 Symp. on Defense and Security
, 2005
"... In this paper, we describe and analyze the performance of two iris-encoding techniques. The first technique is based on Principle Component Analysis (PCA) encoding method while the second technique is a combination of Principal Component Analysis with Independent Component Analysis (ICA) following i ..."
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Cited by 12 (3 self)
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In this paper, we describe and analyze the performance of two iris-encoding techniques. The first technique is based on Principle Component Analysis (PCA) encoding method while the second technique is a combination of Principal Component Analysis with Independent Component Analysis (ICA) following it. Both techniques are applied globally. PCA and ICA are two well known methods used to process a variety of data. Though PCA has been used as a preprocessing step that reduces dimensions for obtaining ICA components for iris, it has never been analyzed in depth as an individual encoding method. In practice PCA and ICA are known as methods that extract global and fine features, respectively. It is shown here that when PCA and ICA methods are used to encode iris images, one of the critical steps required to achieve a good performance is compensation for rotation effect. We further study the effect of varying the image resolution level on the performance of the two encoding methods. The major motivation for this study is the cases in practice where images of the same or different irises taken at different distances have to be compared. The performance of encoding techniques is analyzed using the CASIA dataset. The original images are non-ideal and thus require a sequence of preprocessing steps prior to application of encoding methods. We plot a series of Receiver Operating Characteristics (ROCs) to demonstrate various effects on the performance of the iris-based recognition system implementing PCA and ICA encoding techniques.
Secure iris verification
- In IEEE Acoust., Speech, Signal Process
"... In this paper, we present a novel secure iris verification system, where a transformed version of the iris template instead of the plain reference is stored for protecting the sensitive biometric data. An Error Correcting Code (ECC) technique is adopted to perform the comparison in the transformed d ..."
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Cited by 12 (0 self)
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In this paper, we present a novel secure iris verification system, where a transformed version of the iris template instead of the plain reference is stored for protecting the sensitive biometric data. An Error Correcting Code (ECC) technique is adopted to perform the comparison in the transformed domain. A two-segment method is proposed to execute the feature verification, where a Bose-Chaudhuri-Hochquenghem (BCH) code of a random bit-stream is introduced to eliminate the considerable differences between the features extracted from different scans of irises. A reliable bits selection process during the iris feature generation stage reduces the system error rate from 6.0 % to 0.8%. The appropriate size of the set of reliable bits is determined by investigating the best match between the associated error correct cutting edge and the actual verification accuracy. Index Terms- iris, personal verification, data security 1.
Securing biometric data
- in Distributed Source Coding
"... This chapter discusses the application of distributed source coding techniques to biometric security. A Slepian-Wolf coding system is used to provide a secure means of storing biometric data that provides robust biometric authentication for genuine users and guards against attacks from imposters. A ..."
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Cited by 12 (3 self)
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This chapter discusses the application of distributed source coding techniques to biometric security. A Slepian-Wolf coding system is used to provide a secure means of storing biometric data that provides robust biometric authentication for genuine users and guards against attacks from imposters. A formal quantification of the trade off between security and robustness is provided as a function of the Slepian-Wolf coding rate. Prototype secure biometric designs are presented for both iris and fingerprint modalities. These designs demonstrate that it is feasible to achieve information-theoretic security while not significantly compromising authentication performance (measured in terms of false-rejection and false-acceptance rates) when compared to conventional biometric systems. The methods described in this chapter can be applied to various architectures, including secure biometric authentication for access control and biometric-based key generation for encryption.
