2,495 resources related to Iris Recognition
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No organizations are currently tagged "Iris Recognition"
The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
The 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT) aims to provide a forum that brings together International researchers from academia and practitioners in the industry to meet and exchange ideas and recent research work on all aspects of Information and Communication Technologies including Computing, communication, IOT, LiDAR, Image Analysis, wireless communication and other new technologies
Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.
The 15th IEEE International Conference on Control and Automation (IEEE ICCA 2019) will be held Tuesday through Friday, July 16-19, 2019, in Edinburgh, Scotland. The conference is jointly organized by IEEE Control Systems Chapter, Singapore, and IEEE Control Chapter for United Kingdom and Ireland. It is technically sponsored by IEEE Control Systems Society. It aims to create a forum for scientists and practising engineers throughout the world to present the latest research findings and ideas in the areas of control and automation, and possible contributions toward sustainable development and environment preservation. The conference is featured with the Best Paper Award and the Best Student Paper Award.
No periodicals are currently tagged "Iris Recognition"
IEEE Transactions on Engineering Management, 1979
WIAR 2012; National Workshop on Information Assurance Research, 2012
The major challenge of privacy protection of biometric template is improve the security of the biometric template. Biometric cryptosystems were proposed to hide the cryptographic keys as well as provide security protection of biometrics associated with the traditional biometric systems. A fuzzy commitment scheme is an example of such systems. Moreover, the biometric data cannot be canceled or changed, once ...
2010 2nd European Workshop on Visual Information Processing (EUVIP), 2010
Biometric cryptosystems is a group of emerging technologies that securely bind a digital key to a biometric so that no biometric image or template is stored. Focusing on iris biometrics several approaches have been proposed to bind keys to binary iris-codes where the majority of these approaches are based on the so-called fuzzy commitment scheme. In this work we present ...
2008 19th International Conference on Pattern Recognition, 2008
This paper addresses the issue of counterfeit iris detection, which is a liveness detection problem in biometrics. Fake iris mentioned here refers to iris wearing color contact lens with textures printed onto them. We propose three measures to detect fake iris: measuring iris edge sharpness, applying Iris-Texton feature for characterizing the visual primitives of iris textures and using selected features ...
2010 Third International Conference on Intelligent Networks and Intelligent Systems, 2010
For a driver fatigue warning system, one of the most important problems to solve is eye detection and recognition. The blink information was used to preliminary eye location. Modified Susan operator of eye inner corner extraction to accurate eye location. According to the characteristics of the external environment are less prone to interference from eye inner corner, small template of ...
2012 IEEE Honors - Corporate Innovation Recognition
2011 IEEE Awards Corporate Innovation Recognition - imec
IEEE Low-Power Image Recognition Challenge (LPIRC)
2012 IEEE Honors - IEEE Ernst Weber Engineering Leadership Recognition
Ignite! Session: Blake Lloyd
Low Power Image Recognition: The Challenge Continues
2011 IEEE Awards Ernst Weber Engineering Leadership Recognition - Tze-Chiang Chen
Welcome: Low Power Image Recognition Challenge
2011 IEEE Awards Matt Ettus HKN Eminent Member Recognition
Robotics History: Narratives and Networks Oral Histories: Nils Nilsson
Resistive Coupled VO2 Oscillators for Image Recognition - Elisabetta Corti - ICRC 2018
IBM T.J. Watson Research Center
Dynamic Pattern Recognition and its Application on Non-Stationary Systems
Q&A with Ryan Dailey: IEEE Rebooting Computing Podcast, Episode 12
Capture, Recognition, and Imitation of Anthropomorphic Motion
GHTC 2012 Jim Fruchterman Keynote
Honors 2020: Ramalingam Chellappa Wins the Jack S. Kilby Signal Processing Medal
Takeo Kanade accepts the IEEE Founders Medal - Honors Ceremony 2017
Robotics History: Narratives and Networks Oral Histories: Ray Jarvis
The major challenge of privacy protection of biometric template is improve the security of the biometric template. Biometric cryptosystems were proposed to hide the cryptographic keys as well as provide security protection of biometrics associated with the traditional biometric systems. A fuzzy commitment scheme is an example of such systems. Moreover, the biometric data cannot be canceled or changed, once the biometric template is compromised. Then, all applications depending on this user's biometric data are compromised forever. Thus, it is desirable to have schemes that protect the biometric template as well as generate a new unique pattern if the one being used is lost to be adopted in practical biometric applications. In this paper, we integrate the fuzzy commitment approach with biometrics to achieve a new and simpler type of cancelable biometric scheme in which the template is privacy protected, and multiple fuzzy commitments of the templates can be derived from the same biometric template for the purpose of template renewability.
Biometric cryptosystems is a group of emerging technologies that securely bind a digital key to a biometric so that no biometric image or template is stored. Focusing on iris biometrics several approaches have been proposed to bind keys to binary iris-codes where the majority of these approaches are based on the so-called fuzzy commitment scheme. In this work we present a new approach to constructing iris-based fuzzy commitment schemes. Based on intra-class error analysis iris-codes are rearranged in a way that error correction capacities are exploited more effectively. Experimental results demonstrate the worthiness of our approach.
This paper addresses the issue of counterfeit iris detection, which is a liveness detection problem in biometrics. Fake iris mentioned here refers to iris wearing color contact lens with textures printed onto them. We propose three measures to detect fake iris: measuring iris edge sharpness, applying Iris-Texton feature for characterizing the visual primitives of iris textures and using selected features based on co-occurrence matrix (CM). Extensive testing is carried out on two datasets containing different types of contact lens with totally 640 fake iris images, which demonstrates that Iris-Texton and CM features are effective and robust in anticounterfeit iris. Detailed comparisons with two state-of-the-art methods are also presented, showing that the proposed iris edge sharpness measure acquires a comparable performance with these two methods, while Iris-Texton and CM features outperform the state-of-the-art.
For a driver fatigue warning system, one of the most important problems to solve is eye detection and recognition. The blink information was used to preliminary eye location. Modified Susan operator of eye inner corner extraction to accurate eye location. According to the characteristics of the external environment are less prone to interference from eye inner corner, small template of the eye inner corner was extracted for eye tracking. In the methods of eyes state recognition, the correlation between an online generated template of open eyes in the process of eye tracking and the eye region extracted from the image was used. According to the size of correlation, to further determine the eyes state . The experiment result shows that data quantity disposed is little, realized speed is fast and the accuracy rate of the eye recognition is increased in this method.
In this paper we present a new method for iris texture recognition for the purpose of human identification using statistical analysis of gray-level distribution. Many studies have been aimed at extracting iris features that are unique to every individual. While many have been successful, most requires complex filtering and processing. Our proposed method is based on a simple estimate of the joint probability of a pair of pixel intensities in predetermined relative positions in the image, also called gray-level co- occurrence matrix (GLCM). First, eye images of different human subjects are obtained. The images are then unwrapped or transformed to the polar space and then segmented using dynamic optimal partitioning in order to isolate the iris features from the rest of the image. Contrast normalization is also applied to reduce the effect of non-uniform illumination over different parts of the image. The GLCM of each iris is calculated and normalized to further minimize the effect of constant shift in gray-level intensities. A new representation of the GLCM are then introduced and used to uniquely describe the GLCM. This new representation is based on off-diagonal peaks that depict "busy" areas of rich details. A rule-based approach incorporates these off-diagonal peaks into a feature vector forming the basis for identification. These features extracted for an individual were found to be highly correlated with a variation of his other features and poorly with iris features of other individuals. This suggests that such simple method may be useful in human iris identification
Iris based person identification has become very largely used biometric technology. This paper proposes a technique of feature extraction of iris images, which uses 2-D Gabor filter with four orientations. XOR and SUM operations on the real and imaginary output for each orientation result into a number which is further encoded into bits to give the feature vector. Experiments show that XOR-SUM Code is providing increased recognition accuracy (i.e. GAR) as compared to another feature extraction technique DCT. GAR value for XOR-SUM Code is 96.33% while for DCT, its value is 90.79%.
This paper presents the contribution of custom instructions in image processing and more precisely in our iris recognition application. Benchmarks, comparisons and results between general purpose processor (GPP), custom instruction and dedicated IP show the interest of using custom instructions.
Finger-Knuckle - Print (FKP) is one of the newest biometrics. In this paper, a novel approach has been proposed to segment the Region of Interest (ROI) of a FKP image using the global intensity. This method upgrades the speed and accuracy of segmentation stage, as well as the pace of other steps of the procedure. This has been achieved by employing the area with maximum intensity in ROI extraction, instead of using the creases of the knuckle image. To confirm this improvement, lots of experiments have been performed and the method has been compared with the only existing schemes for ROI extraction suggested by Zhang and Kekre. At the end, the captured ROI images obtained by three methods have been performed on a common procedure of a feature extraction and matching scores, and the results have been compared.
We propose a new method of cooperative development of information systems utilizing virtual machines. This method not only realizes individual operations of systems in each institution, but also is efficient for the institution in shortage of IT-talented staff.
No standards are currently tagged "Iris Recognition"