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.

Iris recognition: an emerging biometric technology

A method of maintaining digital medical records, comprising a step of receiving a medical transaction record (102), encrypted with a key in accordance with a patient-file association. Also comprising a step of accessing the encrypted medical transaction record according to a patient association with the record (111). And further comprising a step of re-encryption of the encrypted accessed medical transaction record with a key associated with an intended recipient of the medical record. The system and method according to the present invention presents a new business model for creation, maintenance, transmission, and use of medical records. The invention also allows financial burdens to be reallocated optimally and equitably, resulting in decreased overall societal cost and providing a successful business model for a database proprietor. Secure entrusted medical records are held in trust by an independent third party on behalf of the patient (113), and serve the medical community at large. Separately encrypted record elements may be aggregated as an information polymer.

Information record infrastructure, system and method

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.

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A system and method for communicating information between a first party and a second party, comprising the steps of receiving, by an intermediary, an identifier of desired information and accounting information for a transaction involving the information from the first party, transmitting an identifier of the first party to the second party, and negotiating, by the intermediary, a comprehension function for obscuring at least a portion of the information communicated between the first party and the second party. The data transmission may be made secure with respect to the intermediary by providing an asymmetric key or direct key exchange for encryption of the communication between the first and second party. The data transmission may be made secure with respect to the second party by maintaining the information in encrypted format at the second party, with the decryption key held only by the intermediary, and transmitting a secure composite of the decryption key and a new encryption key to the second party for transcoding of the data record, and providing the new decryption key to the first party, so that the information transmitted to the first party can be comprehended by it.

System and method for secure three-party communications

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.

A human identification technique using images of the iris and wavelet transform

Iris recognition is achieved by iris acquisition that permits a user to self-position his or her eye (216) into an imager's (200) field of view without the need for any physical contact, spatially locating the data defining that portion of a digitized video image of the user's eye that defines solely the iris thereof without any initial spatial condition of the iris being provided, and pattern matching the spatially located data defining the iris of the user's eye with stored data defining a model iris by employing normalized spatial correlation for first comparing, at each of a plurality of spatial scales, each of distinctive spatial characteristics of the respective irises that are spatially registered with one another to quantitatively determine, at each of the plurality of spatial scales, a goodness value of match at that spatial scale, and then judging whether or not the pattern which manifests solely the iris of the user's eye matches the digital data which manifests solely the model iris in accordance with a certain combination of the quantitatively-determined goodness values of match at each of said plurality of spatial scales.

Automated, non-invasive iris recognition system and method

This paper describes a prototype system for personnel verification based on automated iris recognition. The motivation for this endevour stems from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric measurement. In particular, it is known in the biomedical community 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 the design and operation of such a system. Also presented are the results of an empirical study in which the system exhibits flawless performance in the evaluation of 520 iris images.

A machine-vision system for iris recognition

This paper describes a prototype system for personnel verification based on automated iris recognition. The motivation for this endeavour stems from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric measurement. In particular, it is known in the biomedical community 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 computer vision system. The body of this paper details the design and operation of such a system. Also presented are the results of an empirical study where the system exhibits flawless performance in the evaluation of 520 iris images. >

A system for automated iris recognition

Presents a validation study of an optical-flow method for the rapid estimation of myocardial displacement in magnetic resonance tagged cardiac images. This registration and change visualization (RCV) software uses a hierarchical estimation technique to compute the flow field that describes the warping of an image of one cardiac phase into alignment with the next. This method overcomes the requirement of constant pixel intensity in standard optical-flow methods by preprocessing the input images to reduce any intensity bias which results from the reduction in stripe contrast throughout the cardiac cycle. To validate the method, SPAMM-tagged images were acquired of a silicon gel phantom with simulated rotational motion. The pixel displacement was estimated with the RCV method and the error in pixel tracking was <4% 1000 ms after application of the tags, and after 30/spl deg/ of rotation. An additional study was performed using a SPAMM-tagged multiphase slice of a canine left ventricle. The true displacement was determined using a previously validated active contour model (snakes). The error between methods was 6.7% at end systole. The RCV method has the advantage of tracking all pixels in the image in a substantially shorter period than the snakes method.

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Validation of an optical flow method for tag displacement estimation

Presents an algorithmic approach to the problem of detecting independently moving objects in 3D scenes that are viewed under camera motion. There are two fundamental constraints that can be exploited for the problem: (i) a two- (or multi-)view camera motion constraint (for instance, the epipolar/trilinear constraint), and (ii) a shape constancy constraint. Previous approaches to the problem either only used partial constraints or relied on dense correspondences or flow. We employ both of these fundamental constraints in an algorithm that does not demand a-priori availability of correspondences or flow. Our approach uses the plane-plus-parallax decomposition to enforce the two constraints. It is also demonstrated, for a class of scenes called sparse 3D scenes, in which genuine parallax and independent motions may be confounded, how the plane-plus-parallax decomposition allows progressive introduction and verification of the fundamental constraints. The results of applying the algorithm to some difficult sparse 3D scenes look promising.

Jane C. Asmuth

Papers

Automated, non-invasive iris recognition system and method

A machine-vision system for iris recognition

A system for automated iris recognition

Validation of an optical flow method for tag displacement estimation

Independent motion detection in 3D scenes