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Journal ArticleDOI

Iris recognition: an emerging biometric technology

01 Sep 1997-Vol. 85, Iss: 9, pp 1348-1363
TL;DR: This paper examines automated iris recognition as a biometrically based technology for personal identification and verification from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric assessment.
Abstract: This paper examines automated iris recognition as a biometrically based technology for personal identification and verification. The motivation for this endeavor stems from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric assessment. In particular the biomedical literature suggests that irises are as distinct as fingerprints or patterns of retinal blood vessels. Further, since the iris is an overt body, its appearance is amenable to remote examination with the aid of a machine vision system. The body of this paper details issues in the design and operation of such systems. For the sake of illustration, extant systems are described in some amount of detail.
Citations
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Proceedings Article
01 Jan 1994
TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Abstract: MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

2,134 citations

Proceedings Article
01 Jan 1989
TL;DR: A scheme is developed for classifying the types of motion perceived by a humanlike robot and equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented.
Abstract: A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

2,000 citations

Journal ArticleDOI
TL;DR: The system consists of a novel device for online palmprint image acquisition and an efficient algorithm for fast palmprint recognition, and a robust image coordinate system is defined to facilitate image alignment for feature extraction.
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.

1,416 citations

Proceedings Article
16 Feb 2007
TL;DR: Iris recognition as one of the important method of biometrics-based identification systems and iris recognition algorithm is described and experimental results show that the proposed method has an encouraging performance.
Abstract: In this paper, iris recognition as one of the important method of biometrics-based identification systems and iris recognition algorithm is described. As technology advances and information and intellectual properties are wanted by many unauthorized personnel. As a result many organizations have being searching ways for more secure authentication methods for the user access. In network security there is a vital emphasis on the automatic personal identification. Due to its inherent advantages biometric based verification especially iris identification is gaining a lot of attention. Iris recognition uses iris patterns for personnel identification. The system steps are capturing iris patterns; determining the location of iris boundaries; converting the iris boundary to the stretched polar coordinate system; extracting iris code based on texture analysis. The system has been implemented and tested using dataset of number of samples of iris data with different contrast quality. The developed algorithm performs satisfactorily on the images, provides 93% accuracy. Experimental results show that the proposed method has an encouraging performance.

1,389 citations


Cites background from "Iris recognition: an emerging biome..."

  • ...2 2 2 2 ( ) ( ) / ( ) / 0 0 0 ( , ) i r r i G r e e e ω θ θ α θ θ β θ − − − − − − = (4)...

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  • ...(1) capture the chosen biometric; (2) process the biometric so as to extract and enroll the template; (3)store the template in a local repository, a central repository, or a portable token such as smart card;(4) live-scan the chosen biometric;(5)process the biometric and extract the biometric template;(6)store the reference template;(7) match the scanned 9- Decision 8- Score 7- Matching...

    [...]

Journal ArticleDOI
01 Dec 1983-Nature
TL;DR: In this paper, a considerable collection of totally free of expense Book for people from every single stroll of life has been gathered to gather a sizable library of preferred cost-free as well as paid files.
Abstract: Our goal is always to offer you an assortment of cost-free ebooks too as aid resolve your troubles. We have got a considerable collection of totally free of expense Book for people from every single stroll of life. We have got tried our finest to gather a sizable library of preferred cost-free as well as paid files. Whatever our proffesion, the art of electronics can be excellent resource for reading. Find the existing reports of word, txt, kindle, ppt, zip, pdf, as well as rar in this site. You can definitely check out online or download this book by below. Currently, never miss it. This is really going to save you time and your money in something should think about. If you're seeking then search around for online. Without a doubt there are several these available and a lot of them have the freedom. However no doubt you receive what you spend on. An alternate way to get ideas would be to check another the art of electronics. GO TO THE TECHNICAL WRITING FOR AN EXPANDED TYPE OF THIS THE ART OF ELECTRONICS, ALONG WITH A CORRECTLY FORMATTED VERSION OF THE INSTANCE MANUAL PAGE ABOVE.

1,146 citations

References
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Journal ArticleDOI

40,330 citations


"Iris recognition: an emerging biome..." refers background in this paper

  • ...For example, the ability to locate a face within a range of about a meter and then to point and zoom a camera to acquire an image of the eye region has been demonstrated using available computer vision technology [23]....

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Journal ArticleDOI
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
Abstract: A snake is an energy-minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines and edges. Snakes are active contour models: they lock onto nearby edges, localizing them accurately. Scale-space continuation can be used to enlarge the capture region surrounding a feature. Snakes provide a unified account of a number of visual problems, including detection of edges, lines, and subjective contours; motion tracking; and stereo matching. We have used snakes successfully for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest.

18,095 citations

Journal ArticleDOI

14,009 citations


"Iris recognition: an emerging biome..." refers methods in this paper

  • ...The linear function that provides such a solution is well known and is given by Fisher’s linear discriminant [18], [19]....

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Book
01 Jan 1973
TL;DR: In this article, a unified, comprehensive and up-to-date treatment of both statistical and descriptive methods for pattern recognition is provided, including Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, clustering, preprosessing of pictorial data, spatial filtering, shape description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis.
Abstract: Provides a unified, comprehensive and up-to-date treatment of both statistical and descriptive methods for pattern recognition. The topics treated include Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, clustering, preprosessing of pictorial data, spatial filtering, shape description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis.

13,647 citations