- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Biometric iris recognition using radial basis function neural network
摘要： The consistent and efficient method for the identification of biometrics is the iris recognition in view of the fact that it has richness in texture information. A good number of features performed in the past are built on handcrafted features. The proposed method is based on the feed-forward architecture and uses k-means clustering algorithm for the iris patterns classification. In this paper, segmentation of iris is performed using the circular Hough transform that realizes the iris boundaries in the eye and isolates the region of iris with no eyelashes and other constrictions. Moreover, Daugman's rubber sheet model is used to transform the resultant iris portion into polar coordinates in the process of normalization. A unique iris code is generated by log-Gabor filter to extract the features. The classification is achieved using neural network structures, the feed-forward neural network and the radial basis function neural network. The experiments have been conducted using the Chinese Academy of Sciences Institute of Automation (CASIA) iris database. The proposed system decreases computation time, size of the database and increases the recognition accuracy as compared to the existing algorithms.
关键词： Feed-forward neural network (FNN),Iris segmentation,Normalization,Biometrics,Radial basis function neural network (RBFNN),Iris recognition
更新于2025-09-23 15:23:52
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Exploiting superior CNN-based iris segmentation for better recognition accuracy
摘要： CNN-based iris segmentations have been proven to be superior to traditional iris segmentation techniques in terms of segmentation error metrics. To properly utilize them in a traditional biometric recognition systems requires a parameterization of the iris, based on the generated segmentation, to obtain the normalised iris texture typically used for feature extraction. This is an unsolved problem. We will introduce a method to parameterize CNN based segmentation, bridging the gap between CNN based segmentation and the rubbersheet-transform. The parameterization enables the CNN segmentation as full segmentation step in any regular iris biometric system, or alternatively the segmentation can be utilized as a noise mask for other segmentation methods. Both of these options will be evaluated.
关键词： Iris segmentation,CNN,Parameterization of iris masks,Iris biometrics
更新于2025-09-23 15:23:52
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Human gait recognition based on deterministic learning and data stream of Microsoft Kinect
摘要： Gait is an important biometric technology for human identification at a distance. This study focuses on gait features obtained by Kinect and proposes a new model-based gait recognition method by combining deterministic learning theory and data stream of Microsoft Kinect. Deterministic learning theory is employed to capture the gait dynamics underlying Kinect-based gait parameters. Spatial-temporal gait features can be represented as the gait dynamics underlying the trajectories of spatial-temporal parameters, which can implicitly reflect the temporal changes of silhouette shape. Kinematic gait features can be represented as the gait dynamics underlying the trajectories of kinematic parameters, which can represent the temporal changes of body structure and dynamics. Both spatial-temporal and kinematic cues can be used separately for gait recognition using smallest error principle. They are fused on the decision level to improve the gait recognition performance. Additionally, we discuss how to eliminate the effect of view angle on the proposed method. Experimental results indicate that encouraging recognition accuracy can be achieved.
关键词： deterministic learning,Kinect-based gait features,Gait recognition,biometrics
更新于2025-09-23 15:23:52
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Securing Identities: Biometric Technologies and the Enactment of Human Bodily Differences
摘要： Worldwide, biometrics are quickly becoming the preferred solution to a wide range of problems involving identity checking. Biometrics are claimed to provide more secure identification and verification, because 'the body does not lie.' Yet, every biometric check consists of a process with many intermediate steps, introducing contingency and choice on many levels. In addition, there are underlying normative assumptions regarding human bodies that affect the functioning of biometric systems in highly problematic ways. In recent social science studies, the failures of biometric systems have been interpreted as gendered and racialized biases. A more nuanced understanding of how biometrics and bodily differences intersect draws attention to how bodily differences are produced, used, and problematized during the research and design phases of biometric systems, as well as in their use. In technical engineering research, issues of biometrics' performance and human differences are already transformed into R&D challenges in variously more and less problematic ways. In daily practices of border control, system operators engage in workarounds to make the technology work well with a wide range of users. This shows that claims about 'inherent whiteness' of biometrics should be adjusted: relationships between biometric technologies, gender and ethnicity are emergent, multiple and complex. Moreover, from the viewpoint of theorizing gender and ethnicity, biometrics' difficulties in correctly recognising pre-defined categories of gender or ethnicity may be less significant than its involvement in producing and enacting (new) gender and ethnic classifications and identities.
关键词： identity,ethnicity,enactment,Biometrics,border management
更新于2025-09-23 15:23:52
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[ACM Press the 2018 International Conference - Jeju, Republic of Korea (2018.04.27-2018.04.29)] Proceedings of the 2018 International Conference on Information Science and System - ICISS '18 - A Review on Iris Recognition in Non-Cooperative Environment
摘要： Nowadays, researcher is focus in developing reliable iris recognition systems for non-cooperative situations. The demand for iris recognition is increasing due to its reliability, accuracy and uniqueness. There are major factors involved in unconstrained environment such as obstruction by eyelids, eyelashes, glass frames, hair, off-angle, presence of contact lenses, poor illumination, motion blur, lighting and specular reflections, partially eye image, etc. The performance of the iris will be deteriorated and this results in lower recognition rate. In this paper, an overview of iris recognition for noisy imaging environments is presented included various related databases for iris recognition systems.
关键词： Biometrics,iris recognition,non-cooperative
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - A low-cost Multi-Fingervein Verification System
摘要： Fingervein based biometric verification systems are widely used in various access control applications due to their accuracy and reliability. However, almost all existing fingervein systems scan only one finger at a time and this may not be a reliable solution for more secured applications demanding higher accuracy in verification and reliability. In this work, we propose a new multi-fingervein capture system that can simultaneously capture three different fingers in a single capture instance. The developed fingervein sensor is validated for operational purposes through images captured from 20 unique identities(subjects) with 600 fingervein images. The suitability of captured images for biometric applications is vetted through the use of four different state-of-the-art verification algorithms. The results are benchmarked and compared using individual fingervein data and in addition the employability of score level fusion is presented to improve the performance. The reported results in this article support the anticipated increase in performance of the multi-fingervein verification.
关键词： authentication,identification,fingervein,Biometrics,person verification
更新于2025-09-23 15:22:29
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[Lecture Notes in Computer Science] Pattern Recognition and Computer Vision Volume 11256 (First Chinese Conference, PRCV 2018, Guangzhou, China, November 23-26, 2018, Proceedings, Part I) || Hand Dorsal Vein Recognition Based on Deep Hash Network
摘要： As a unique biometric technology that has emerged in recent decades, hand dorsal vein recognition has received increasing attention due to its higher safety and convenience. In order to further improve the recognition accuracy, in this paper we propose an end-to-end method for recognizing Hand dorsal vein Based on Deep hash network (DHN), called HBD. The hand dorsal vein image is input into the simpli?ed Convolutional Neural Networks-Fast (SCNN-F) to obtain convolution features. At the last fully connected layer, for the outputs of 128 neurons, sgn function is used to encode each image as 128-bit code. By comparing the distances between images after coding, it can be judged whether they are from the same person. Using a special loss function and training strategy, we verify the effectiveness of HBD on the NCUT, GPDS, and NCUT+GPDS database, respectively. The experimental results show that the HBD method can achieve comparable accuracy to the state-of-the-arts. In NCUT database, when the ratio of training and test set is 7:3, the Equal Error Rate (EER) of the test set is 0.08%, which is an order of magnitude lower than other algorithms. More importantly, due to the adoption of a simpler network structure and hash coding, HBD operates more ef?ciently and has superior performance gains over other deep learning methods while ensuring the accuracy.
关键词： Hand dorsal vein recognition,Deep hash network,Biometrics
更新于2025-09-23 15:21:21
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[IEEE 2019 IEEE SENSORS - Montreal, QC, Canada (2019.10.27-2019.10.30)] 2019 IEEE SENSORS - Optical sensor based on pseudo-random diffractive optical elements for reliable gesture reconstruction
摘要： Biometric template aging is defined as an increase in recognition error rate with increased time since enrollment. It is believed that template aging does not occur for iris recognition. Several research groups, however, have recently reported experimental results showing that iris template aging does occur. This template aging effect manifests as a shift in the authentic distribution, resulting in an increased false non-match rate. Analyzing results from a three-year time-lapse data set, we find ～ 150% increase in the false non-match rate at a decision threshold representing a one in two million false match rate. We summarize several known elements of eye aging that could contribute to template aging, including age-related change in pupil dilation. Finally, we discuss various steps that can control the template aging effect in typical identity verification applications.
关键词： false non-match rate,iris recognition,Biometrics,error probability,template aging
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Oxygen Concentration Dependence of Photovoltaic Properties of Intermediate Band Solar Cells based on Cl-doped ZnTeO
摘要： We present a large-scale study exploring the capability of temporal deep neural networks to interpret natural human kinematics and introduce the first method for active biometric authentication with mobile inertial sensors. At Google, we have created a first-of-its-kind data set of human movements, passively collected by 1500 volunteers using their smartphones daily over several months. We compare several neural architectures for efficient learning of temporal multi-modal data representations, propose an optimized shift-invariant dense convolutional mechanism, and incorporate the discriminatively trained dynamic features in a probabilistic generative framework taking into account temporal characteristics. Our results demonstrate that human kinematics convey important information about user identity and can serve as a valuable component of multi-modal authentication systems. Finally, we demonstrate that the proposed model can also be successfully applied in a visual context.
关键词： recurrent neural networks,mobile computing,biometrics (access control),Authentication,learning
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE International Symposium on Phased Array System & Technology (PAST) - Waltham, MA, USA (2019.10.15-2019.10.18)] 2019 IEEE International Symposium on Phased Array System & Technology (PAST) - Dual-Polarized 28-GHz Air-Filled SIW Phased Antenna Array for Next-Generation Cellular Systems
摘要： Biometric template aging is defined as an increase in recognition error rate with increased time since enrollment. It is believed that template aging does not occur for iris recognition. Several research groups, however, have recently reported experimental results showing that iris template aging does occur. This template aging effect manifests as a shift in the authentic distribution, resulting in an increased false non-match rate. Analyzing results from a three-year time-lapse data set, we find ～ 150% increase in the false non-match rate at a decision threshold representing a one in two million false match rate. We summarize several known elements of eye aging that could contribute to template aging, including age-related change in pupil dilation. Finally, we discuss various steps that can control the template aging effect in typical identity verification applications.
关键词： iris recognition,Biometrics,error probability,false non-match rate,template aging
更新于2025-09-23 15:19:57