Results 1 - 10 of 587

How Iris Recognition Works

by John Daugman , 2003
"... Algorithms developed by the author for recogniz-ing persons by their iris patterns have now been tested in six field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statis-tical independence on iris phase st ..."
Abstract - Cited by 495 (4 self) - Add to MetaCart
Algorithms developed by the author for recogniz-ing persons by their iris patterns have now been tested in six field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statis-tical independence on iris phase structure encoded by multi-scale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 244 degrees of freedom and gen-erates a discrimination entropy of about 3.2 bits/mm over the iris, enabling real-time decisions about per-sonal identity with extremely high confidence. The high confidence levels are important because they al-low very large databases to be searched exhaustively (one-to-many “identification mode”) without making any false matches, despite so many chances. Biomet-rics lacking this property can only survive one-to-one (“verification”) or few comparisons. This paper ex-plains the algorithms for iris recognition, and presents the results of 2.3 million comparisons among eye im-ages acquired in trials in Britain, the USA, and Japan. 1
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A Fuzzy Commitment Scheme

by Ari Juels, Martin Wattenberg - ACM CCS'99 , 1999
"... We combine well-known techniques from the areas of errorcorrecting codes and cryptography to achieve a new type of cryptographic primitive that we refer to as a fuzzy commitment scheme. Like a conventional cryptographic commitment scheme, our fuzzy commitment scheme is both concealing and binding: i ..."
Abstract - Cited by 327 (1 self) - Add to MetaCart
We combine well-known techniques from the areas of errorcorrecting codes and cryptography to achieve a new type of cryptographic primitive that we refer to as a fuzzy commitment scheme. Like a conventional cryptographic commitment scheme, our fuzzy commitment scheme is both concealing and binding: it is infeasible for an attacker to learn the committed value, and also for the committer to decommit a value in more than one way. In a conventional scheme, a commitment must be opened using a unique witness, which acts, essentially, as a decryption key. By contrast, our scheme is fuzzy in the sense that it accepts a witness that is close to the original encrypting witness in a suitable metric, but not necessarily identical. This characteristic of our fuzzy commitment scheme makes it useful for applications such as biometric authentication systems, in which data is subject to random noise. Because the scheme is tolerant of error, it is capable of protecting biometric data just as conventional cryptographic techniques, like hash functions, are used to protect alphanumeric passwords. This addresses a major outstanding problem in the theory of biometric authentication. We prove the security characteristics of our fuzzy commitment scheme relative to the properties of an underlying cryptographic hash function.

Recognition without Correspondence using Multidimensional Receptive Field Histograms

by Bernt Schiele, James L. Crowley - International Journal of Computer Vision , 2000
"... . The appearance of an object is composed of local structure. This local structure can be described and characterized by a vector of local features measured by local operators such as Gaussian derivatives or Gabor filters. This article presents a technique where appearances of objects are represente ..."
Abstract - Cited by 257 (20 self) - Add to MetaCart
. The appearance of an object is composed of local structure. This local structure can be described and characterized by a vector of local features measured by local operators such as Gaussian derivatives or Gabor filters. This article presents a technique where appearances of objects are represented by the joint statistics of such local neighborhood operators. As such, this represents a new class of appearance based techniques for computer vision. Based on joint statistics, the paper develops techniques for the identification of multiple objects at arbitrary positions and orientations in a cluttered scene. Experiments show that these techniques can identify over 100 objects in the presence of major occlusions. Most remarkably, the techniques have low complexity and therefore run in real-time. 1. Introduction The paper proposes a framework for the statistical representation of the appearance of arbitrary 3D objects. This representation consists of a probability density function or jo...
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A Human Identification Technique Using Images of the Iris and Wavelet Transform

by W. W. Boles, B. Boashash - IEEE Transactions on Signal Processing , 1998
"... Abstract—A new approach for recognizing the iris of the human eye is presented. Zero-crossings of the wavelet transform at various resolution levels are calculated over concentric circles on the iris, and the resulting one-dimensional (1-D) signals are compared with model features using different di ..."
Abstract - Cited by 197 (0 self) - Add to MetaCart
Abstract—A new approach for recognizing the iris of the human eye is presented. Zero-crossings of the wavelet transform at various resolution levels are calculated over concentric circles on the iris, and the resulting one-dimensional (1-D) signals are compared with model features using different dissimilarity functions. Index Terms — Human identification, iris recognition, wavelet transform. I.
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A Review of Content-Based Image Retrieval Systems in Medical Applications -- Clinical Benefits and Future Directions

by Henning Müller, Nicolas Michoux, David Bandon, Antoine Geissbuhler
"... ..."
Abstract - Cited by 194 (12 self) - Add to MetaCart
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Integrating Faces and Fingerprints for Personal Identification

by Lin Hong, Anil Jain - IEEE transactions on pattern analysis and machine intelligence , 1998
"... Abstract—An automatic personal identification system based solely on fingerprints or faces is often not able to meet the system performance requirements. Face recognition is fast but not extremely reliable, while fingerprint verification is reliable but inefficient in database retrieval. We have dev ..."
Abstract - Cited by 179 (14 self) - Add to MetaCart
Abstract—An automatic personal identification system based solely on fingerprints or faces is often not able to meet the system performance requirements. Face recognition is fast but not extremely reliable, while fingerprint verification is reliable but inefficient in database retrieval. We have developed a prototype biometric system which integrates faces and fingerprints. The system overcomes the limitations of face recognition systems as well as fingerprint verification systems. The integrated prototype system operates in the identification mode with an admissible response time. The identity established by the system is more reliable than the identity established by a face recognition system. In addition, the proposed decision fusion scheme enables performance improvement by integrating multiple cues with different confidence measures. Experimental results demonstrate that our system performs very well. It meets the response time as well as the accuracy requirements. Index Terms—Biometrics, fingerprint matching, minutiae, face recognition, eigenface, decision fusion.
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Online palmprint identification

by David Zhang, Senior Member, Wai-kin Kong, Jane You, Michael Wong - IEEE Trans. Pattern Anal. Mach. Intell , 2003
"... Abstract—Biometrics-based personal identification is regarded as an effective method for automatically recognizing, with a high confidence, a person’s identity. This paper presents a new biometric approach to online personal identification using palmprint technology. In contrast to the existing meth ..."
Abstract - Cited by 174 (37 self) - Add to MetaCart
Abstract—Biometrics-based personal identification is regarded as an effective method for automatically recognizing, with a high confidence, a person’s identity. This paper presents a new biometric approach to online personal identification using palmprint technology. In contrast to the existing methods, our online palmprint identification system employs low-resolution palmprint images to achieve effective personal identification. The system consists of two parts: a novel device for online palmprint image acquisition and an efficient algorithm for fast palmprint recognition. A robust image coordinate system is defined to facilitate image alignment for feature extraction. In addition, a 2D Gabor phase encoding scheme is proposed for palmprint feature extraction and representation. The experimental results demonstrate the feasibility of the proposed system. Index Terms—Biometrics, online palmprint identification, texture analysis, low-resolution image. 1

Personal Identification Based on Iris Texture Analysis

by Li Ma, Tieniu Tan, Senior Member, Yunhong Wang, Dexin Zhang - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2003
"... With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention over the past decade. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. ..."
Abstract - Cited by 162 (11 self) - Add to MetaCart
With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention over the past decade. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. This paper focuses on the last issue and describes a new scheme for iris recognition from an image sequence. We first assess the quality of each image in the input sequence and select a clear iris image from such a sequence for subsequent recognition. A bank of spatial filters, whose kernels are suitable for iris recognition, is then used to capture local characteristics of the iris so as to produce discriminating texture features. Experimental results show that the proposed method has an encouraging performance. In particular, a comparative study of existing methods for iris recognition is conducted on an iris image database including 2,255 sequences from 213 subjects. Conclusions based on such a comparison using a nonparametric statistical method (the bootstrap) provide useful information for further research.
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Efficient Iris Recognition by Characterizing Key Local Variations

by Li Ma, Tieniu Tan, Yunhong Wang, Dexin Zhang - IEEE Trans. on Image Processing , 2004
"... Abstract—Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper ..."
Abstract - Cited by 159 (8 self) - Add to MetaCart
Abstract—Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image structure, are utilized to represent the characteristics of the iris. The whole procedure of feature extraction includes two steps: 1) a set of one-dimensional intensity signals is constructed to effectively characterize the most important information of the original two-dimensional image; 2) using a particular class of wavelets, a position sequence of local sharp variation points in such signals is recorded as features. We also present a fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences. Experimental results on 2 255 iris images show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature. Index Terms—Biometrics, iris recognition, local sharp variations, personal identification, transient signal analysis, wavelet transform. I.
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Biometric Cryptosystems: Issues and Challenges

by Umut Uludag, Sharath Pankanti, Salil Prabhakar, Anil K. Jain - PROCEEDINGS OF THE IEEE , 2004
"... ... In this paper, we present various methods that monolithically bind a cryptographic key with the biometric template of a user stored in the database in such a way that the key cannot be revealed without a successful biometric authentication. We assess the performance of one of these biometric key ..."
Abstract - Cited by 155 (8 self) - Add to MetaCart
... In this paper, we present various methods that monolithically bind a cryptographic key with the biometric template of a user stored in the database in such a way that the key cannot be revealed without a successful biometric authentication. We assess the performance of one of these biometric key binding/generation algorithms using the fingerprint biometric. We illustrate the challenges involved in biometric key generation primarily due to drastic acquisition variations in the representation of a biometric identifier and the imperfect nature of biometric feature extraction and matching algorithms. We elaborate on the suitability of these algorithms for the digital rights management systems.