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Sample records for multimodal biometrics feature

  1. Fusion of Multimodal Biometrics using Feature and Score Level Fusion

    OpenAIRE

    Mohana Prakash, S.; Betty, P.; Sivanarulselvan, K.

    2016-01-01

    Biometrics is used to uniquely identify a person‘s individual based on physical and behavioural characteristics. Unimodal biometric system contains various problems such as degree of freedom, spoof attacks, non-universality, noisy data and error rates. Multimodal biometrics is introduced to overcome the limitations in Unimodal biometrics. The presented methodology extracts the features of four biometric traits such as fingerprint, palm, iris and retina. Then extracted features are fused in th...

  2. Simplified Multimodal Biometric Identification

    Directory of Open Access Journals (Sweden)

    Abhijit Shete

    2014-03-01

    Full Text Available Multibiometric systems are expected to be more reliable than unimodal biometric systems for personal identification due to the presence of multiple, fairly independent pieces of evidence e.g. Unique Identification Project "Aadhaar" of Government of India. In this paper, we present a novel wavelet based technique to perform fusion at the feature level and score level by considering two biometric modalities, face and fingerprint. The results indicate that the proposed technique can lead to substantial improvement in multimodal matching performance. The proposed technique is simple because of no preprocessing of raw biometric traits as well as no feature and score normalization.

  3. A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Arvind Selwal

    2016-09-01

    Full Text Available Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. To minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work a new scheme is proposed to secure template during feature fusion level. Scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is cancelable and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. Developed scheme removes the problem of an attacker learning the original minutia position in fingerprint and various measurements of hand geometry. Given scheme provides improved performance of the system with reduction in false accept rate and improvement in genuine accept rate.

  4. Extended feature-fusion guidelines to improve image-based multi-modal biometrics

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-09-01

    Full Text Available The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint...

  5. Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

    Directory of Open Access Journals (Sweden)

    Dane Brown

    2017-07-01

    Full Text Available The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our recent work, are extended by adding a new face segmentation method and the support vector machine classifier. The new face segmentation method improves the face identification equal error rate (EER by 10%. The support vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.

  6. A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

    OpenAIRE

    Arvind Selwal; Sunil Kumar Gupta; Surender Kumar

    2016-01-01

    Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric mod...

  7. Score level fusion scheme based on adaptive local Gabor features for face-iris-fingerprint multimodal biometric

    Science.gov (United States)

    He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Chen, Ying

    2014-05-01

    A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal biometric systems. We have introduced a fusion scheme to gain a better understanding and fusion method for a face-iris-fingerprint multimodal biometric system. In our case, we use particle swarm optimization to train a set of adaptive Gabor filters in order to achieve the proper Gabor basic functions for each modality. For a closer analysis of texture information, two different local Gabor features for each modality are produced by the corresponding Gabor coefficients. Next, all matching scores of the two Gabor features for each modality are projected to a single-scalar score via a trained, supported, vector regression model for a final decision. A large-scale dataset is formed to validate the proposed scheme using the Facial Recognition Technology database-fafb and CASIA-V3-Interval together with FVC2004-DB2a datasets. The experimental results demonstrate that as well as achieving further powerful local Gabor features of multimodalities and obtaining better recognition performance by their fusion strategy, our architecture also outperforms some state-of-the-art individual methods and other fusion approaches for face-iris-fingerprint multimodal biometric systems.

  8. Face-iris multimodal biometric scheme based on feature level fusion

    Science.gov (United States)

    Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing; He, Fei

    2015-11-01

    Unlike score level fusion, feature level fusion demands all the features extracted from unimodal traits with high distinguishability, as well as homogeneity and compatibility, which is difficult to achieve. Therefore, most multimodal biometric research focuses on score level fusion, whereas few investigate feature level fusion. We propose a face-iris recognition method based on feature level fusion. We build a special two-dimensional-Gabor filter bank to extract local texture features from face and iris images, and then transform them by histogram statistics into an energy-orientation variance histogram feature with lower dimensions and higher distinguishability. Finally, through a fusion-recognition strategy based on principal components analysis and support vector machine (FRSPS), feature level fusion and one-to-n identification are accomplished. The experimental results demonstrate that this method can not only effectively extract face and iris features but also provide higher recognition accuracy. Compared with some state-of-the-art fusion methods, the proposed method has a significant performance advantage.

  9. A robust probabilistic collaborative representation based classification for multimodal biometrics

    Science.gov (United States)

    Zhang, Jing; Liu, Huanxi; Ding, Derui; Xiao, Jianli

    2018-04-01

    Most of the traditional biometric recognition systems perform recognition with a single biometric indicator. These systems have suffered noisy data, interclass variations, unacceptable error rates, forged identity, and so on. Due to these inherent problems, it is not valid that many researchers attempt to enhance the performance of unimodal biometric systems with single features. Thus, multimodal biometrics is investigated to reduce some of these defects. This paper proposes a new multimodal biometric recognition approach by fused faces and fingerprints. For more recognizable features, the proposed method extracts block local binary pattern features for all modalities, and then combines them into a single framework. For better classification, it employs the robust probabilistic collaborative representation based classifier to recognize individuals. Experimental results indicate that the proposed method has improved the recognition accuracy compared to the unimodal biometrics.

  10. Multimodal Biometric System- Fusion Of Face And Fingerprint Biometrics At Match Score Fusion Level

    Directory of Open Access Journals (Sweden)

    Grace Wangari Mwaura

    2017-04-01

    Full Text Available Biometrics has developed to be one of the most relevant technologies used in Information Technology IT security. Unimodal biometric systems have a variety of problems which decreases the performance and accuracy of these system. One way to overcome the limitations of the unimodal biometric systems is through fusion to form a multimodal biometric system. Generally biometric fusion is defined as the use of multiple types of biometric data or ways of processing the data to improve the performance of biometric systems. This paper proposes to develop a model for fusion of the face and fingerprint biometric at the match score fusion level. The face and fingerprint unimodal in the proposed model are built using scale invariant feature transform SIFT algorithm and the hamming distance to measure the distance between key points. To evaluate the performance of the multimodal system the FAR and FRR of the multimodal are compared along those of the individual unimodal systems. It has been established that the multimodal has a higher accuracy of 92.5 compared to the face unimodal system at 90 while the fingerprint unimodal system is at 82.5.

  11. Multimodal biometric approach for cancelable face template generation

    Science.gov (United States)

    Paul, Padma Polash; Gavrilova, Marina

    2012-06-01

    Due to the rapid growth of biometric technology, template protection becomes crucial to secure integrity of the biometric security system and prevent unauthorized access. Cancelable biometrics is emerging as one of the best solutions to secure the biometric identification and verification system. We present a novel technique for robust cancelable template generation algorithm that takes advantage of the multimodal biometric using feature level fusion. Feature level fusion of different facial features is applied to generate the cancelable template. A proposed algorithm based on the multi-fold random projection and fuzzy communication scheme is used for this purpose. In cancelable template generation, one of the main difficulties is keeping interclass variance of the feature. We have found that interclass variations of the features that are lost during multi fold random projection can be recovered using fusion of different feature subsets and projecting in a new feature domain. Applying the multimodal technique in feature level, we enhance the interclass variability hence improving the performance of the system. We have tested the system for classifier fusion for different feature subset and different cancelable template fusion. Experiments have shown that cancelable template improves the performance of the biometric system compared with the original template.

  12. Developing a multimodal biometric authentication system using soft computing methods.

    Science.gov (United States)

    Malcangi, Mario

    2015-01-01

    Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.

  13. An Efficient Human Identification through MultiModal Biometric System

    Directory of Open Access Journals (Sweden)

    K. Meena

    Full Text Available ABSTRACT Human identification is essential for proper functioning of society. Human identification through multimodal biometrics is becoming an emerging trend, and one of the reasons is to improve recognition accuracy. Unimodal biometric systems are affected by various problemssuch as noisy sensor data,non-universality, lack of individuality, lack of invariant representation and susceptibility to circumvention.A unimodal system has limited accuracy. Hence, Multimodal biometric systems by combining more than one biometric feature in different levels are proposed in order to enhance the performance of the system. A supervisor module combines the different opinions or decisions delivered by each subsystem and then make a final decision. In this paper, a multimodal biometrics authentication is proposed by combining face, iris and finger features. Biometric features are extracted by Local Derivative Ternary Pattern (LDTP in Contourlet domain and an extensive evaluation of LDTP is done using Support Vector Machine and Nearest Neighborhood Classifier. The experimental evaluations are performed on a public dataset demonstrating the accuracy of the proposed system compared with the existing systems. It is observed that, the combination of face, fingerprint and iris gives better performance in terms of accuracy, False Acceptance Rate, False Rejection Rate with minimum computation time.

  14. Multimodal Biometric System- Fusion Of Face And Fingerprint Biometrics At Match Score Fusion Level

    OpenAIRE

    Grace Wangari Mwaura; Prof. Waweru Mwangi; Dr. Calvins Otieno

    2017-01-01

    Biometrics has developed to be one of the most relevant technologies used in Information Technology IT security. Unimodal biometric systems have a variety of problems which decreases the performance and accuracy of these system. One way to overcome the limitations of the unimodal biometric systems is through fusion to form a multimodal biometric system. Generally biometric fusion is defined as the use of multiple types of biometric data or ways of processing the data to improve the performanc...

  15. Quality dependent fusion of intramodal and multimodal biometric experts

    Science.gov (United States)

    Kittler, J.; Poh, N.; Fatukasi, O.; Messer, K.; Kryszczuk, K.; Richiardi, J.; Drygajlo, A.

    2007-04-01

    We address the problem of score level fusion of intramodal and multimodal experts in the context of biometric identity verification. We investigate the merits of confidence based weighting of component experts. In contrast to the conventional approach where confidence values are derived from scores, we use instead raw measures of biometric data quality to control the influence of each expert on the final fused score. We show that quality based fusion gives better performance than quality free fusion. The use of quality weighted scores as features in the definition of the fusion functions leads to further improvements. We demonstrate that the achievable performance gain is also affected by the choice of fusion architecture. The evaluation of the proposed methodology involves 6 face and one speech verification experts. It is carried out on the XM2VTS data base.

  16. Multi-modal Behavioural Biometric Authentication for Mobile Devices

    OpenAIRE

    Saevanee , Hataichanok; Clarke , Nathan ,; Furnell , Steven ,

    2012-01-01

    Part 12: Authentication and Delegation; International audience; The potential advantages of behavioural biometrics are that they can be utilised in a transparent (non-intrusive) and continuous authentication system. However, individual biometric techniques are not suited to all users and scenarios. One way to increase the reliability of transparent and continuous authentication systems is create a multi-modal behavioural biometric authentication system. This research investigated three behavi...

  17. Fourier domain asymmetric cryptosystem for privacy protected multimodal biometric security

    Science.gov (United States)

    Choudhury, Debesh

    2016-04-01

    We propose a Fourier domain asymmetric cryptosystem for multimodal biometric security. One modality of biometrics (such as face) is used as the plaintext, which is encrypted by another modality of biometrics (such as fingerprint). A private key is synthesized from the encrypted biometric signature by complex spatial Fourier processing. The encrypted biometric signature is further encrypted by other biometric modalities, and the corresponding private keys are synthesized. The resulting biometric signature is privacy protected since the encryption keys are provided by the human, and hence those are private keys. Moreover, the decryption keys are synthesized using those private encryption keys. The encrypted signatures are decrypted using the synthesized private keys and inverse complex spatial Fourier processing. Computer simulations demonstrate the feasibility of the technique proposed.

  18. Joint sparse representation for robust multimodal biometrics recognition.

    Science.gov (United States)

    Shekhar, Sumit; Patel, Vishal M; Nasrabadi, Nasser M; Chellappa, Rama

    2014-01-01

    Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing fusion-based methods.

  19. Biometric Features in Person Recognition Systems

    Directory of Open Access Journals (Sweden)

    Edgaras Ivanovas

    2011-03-01

    Full Text Available Lately a lot of research effort is devoted for recognition of a human being using his biometric characteristics. Biometric recognition systems are used in various applications, e. g., identification for state border crossing or firearm, which allows only enrolled persons to use it. In this paper biometric characteristics and their properties are reviewed. Development of high accuracy system requires distinctive and permanent characteristics, whereas development of user friendly system requires collectable and acceptable characteristics. It is showed that properties of biometric characteristics do not influence research effort significantly. Properties of biometric characteristic features and their influence are discussed.Article in Lithuanian

  20. A Novel Multimodal Biometrics Recognition Model Based on Stacked ELM and CCA Methods

    Directory of Open Access Journals (Sweden)

    Jucheng Yang

    2018-04-01

    Full Text Available Multimodal biometrics combine a variety of biological features to have a significant impact on identification performance, which is a newly developed trend in biometrics identification technology. This study proposes a novel multimodal biometrics recognition model based on the stacked extreme learning machines (ELMs and canonical correlation analysis (CCA methods. The model, which has a symmetric structure, is found to have high potential for multimodal biometrics. The model works as follows. First, it learns the hidden-layer representation of biological images using extreme learning machines layer by layer. Second, the canonical correlation analysis method is applied to map the representation to a feature space, which is used to reconstruct the multimodal image feature representation. Third, the reconstructed features are used as the input of a classifier for supervised training and output. To verify the validity and efficiency of the method, we adopt it for new hybrid datasets obtained from typical face image datasets and finger-vein image datasets. Our experimental results demonstrate that our model performs better than traditional methods.

  1. Unobtrusive Multimodal Biometric Authentication: The HUMABIO Project Concept

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    Evangelos Bekiaris

    2008-03-01

    Full Text Available Human Monitoring and Authentication using Biodynamic Indicators and Behavioural Analysis (HUMABIO (2007 is an EU Specific Targeted Research Project (STREP where new types of biometrics are combined with state of the art sensorial technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system which utilizes a biodynamic physiological profile, unique for each individual, and advancements of the state-of-the art in behavioural and other biometrics, such as face, speech, gait recognition, and seat-based anthropometrics. Several shortcomings in biometric authentication will be addressed in the course of HUMABIO which will provide the basis for improving existing sensors, develop new algorithms, and design applications, towards creating new, unobtrusive biometric authentication procedures in security sensitive, controlled environments. This paper presents the concept of this project, describes its unobtrusive authentication demonstrator, and reports some preliminary results.

  2. Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization

    Directory of Open Access Journals (Sweden)

    Jing-Yu Yang

    2012-04-01

    Full Text Available When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person’s overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA. Specifically, one person’s different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance.

  3. Palmprint and face multi-modal biometric recognition based on SDA-GSVD and its kernelization.

    Science.gov (United States)

    Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

    2012-01-01

    When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance.

  4. Palmprint and Face Multi-Modal Biometric Recognition Based on SDA-GSVD and Its Kernelization

    Science.gov (United States)

    Jing, Xiao-Yuan; Li, Sheng; Li, Wen-Qian; Yao, Yong-Fang; Lan, Chao; Lu, Jia-Sen; Yang, Jing-Yu

    2012-01-01

    When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person's overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person's different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance. PMID:22778600

  5. Handwriting: Feature Correlation Analysis for Biometric Hashes

    Science.gov (United States)

    Vielhauer, Claus; Steinmetz, Ralf

    2004-12-01

    In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation), the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.

  6. Handwriting: Feature Correlation Analysis for Biometric Hashes

    Directory of Open Access Journals (Sweden)

    Ralf Steinmetz

    2004-04-01

    Full Text Available In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation, the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.

  7. Reliability-Based Decision Fusion in Multimodal Biometric Verification Systems

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    Kryszczuk Krzysztof

    2007-01-01

    Full Text Available We present a methodology of reliability estimation in the multimodal biometric verification scenario. Reliability estimation has shown to be an efficient and accurate way of predicting and correcting erroneous classification decisions in both unimodal (speech, face, online signature and multimodal (speech and face systems. While the initial research results indicate the high potential of the proposed methodology, the performance of the reliability estimation in a multimodal setting has not been sufficiently studied or evaluated. In this paper, we demonstrate the advantages of using the unimodal reliability information in order to perform an efficient biometric fusion of two modalities. We further show the presented method to be superior to state-of-the-art multimodal decision-level fusion schemes. The experimental evaluation presented in this paper is based on the popular benchmarking bimodal BANCA database.

  8. A biometric identification system based on eigenpalm and eigenfinger features.

    Science.gov (United States)

    Ribaric, Slobodan; Fratric, Ivan

    2005-11-01

    This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).

  9. Comparison of DCT, SVD and BFOA based multimodal biometric watermarking system

    Directory of Open Access Journals (Sweden)

    S. Anu H. Nair

    2015-12-01

    Full Text Available Digital image watermarking is a major domain for hiding the biometric information, in which the watermark data are made to be concealed inside a host image imposing imperceptible change in the picture. Due to the advance in digital image watermarking, the majority of research aims to make a reliable improvement in robustness to prevent the attack. The reversible invisible watermarking scheme is used for fingerprint and iris multimodal biometric system. A novel approach is used for fusing different biometric modalities. Individual unique modalities of fingerprint and iris biometric are extracted and fused using different fusion techniques. The performance of different fusion techniques is evaluated and the Discrete Wavelet Transform fusion method is identified as the best. Then the best fused biometric template is watermarked into a cover image. The various watermarking techniques such as the Discrete Cosine Transform (DCT, Singular Value Decomposition (SVD and Bacterial Foraging Optimization Algorithm (BFOA are implemented to the fused biometric feature image. Performance of watermarking systems is compared using different metrics. It is found that the watermarked images are found robust over different attacks and they are able to reverse the biometric template for Bacterial Foraging Optimization Algorithm (BFOA watermarking technique.

  10. Multimodal biometric system using rank-level fusion approach.

    Science.gov (United States)

    Monwar, Md Maruf; Gavrilova, Marina L

    2009-08-01

    In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.

  11. Biometric features and privacy : condemned, based upon your finger print

    NARCIS (Netherlands)

    Bullee, Jan-Willem; Veldhuis, Raymond N.J.

    What information is available in biometric features besides that needed for the biometric recognition process? What if a biometric feature contains Personally Identifiable Information? Will the whole biometric system become a threat to privacy? This paper is an attempt to quantifiy the link between

  12. Multimodal Authentication - Biometric Password And Steganography

    Directory of Open Access Journals (Sweden)

    Alvin Prasad

    2017-06-01

    Full Text Available Security is a major concern for everyone be it individuals or organizations. As the nature of information systems is becoming distributed securing them is becoming difficult as well. New applications are developed by researchers and developers to counter security issues but as soon as the application is released new attacks are formed to bypass the application. Kerberos is an authentication protocol which helps in to verify and validate a user to a server. As it is a widely used protocol minimizing or preventing the password attack is important. In this research we have analyzed the Kerberos protocol and suggested some ideas which can be considered while updating Kerberos to prevent the password attack. In the proposed solution we are suggesting to use password and biometric technique while registering on the network to enjoy the services and a combination of cryptography and steganography technique while communicating back to the user.

  13. Multimodal biometric method that combines veins, prints, and shape of a finger

    Science.gov (United States)

    Kang, Byung Jun; Park, Kang Ryoung; Yoo, Jang-Hee; Kim, Jeong Nyeo

    2011-01-01

    Multimodal biometrics provides high recognition accuracy and population coverage by using various biometric features. A single finger contains finger veins, fingerprints, and finger geometry features; by using multimodal biometrics, information on these multiple features can be simultaneously obtained in a short time and their fusion can outperform the use of a single feature. This paper proposes a new finger recognition method based on the score-level fusion of finger veins, fingerprints, and finger geometry features. This research is novel in the following four ways. First, the performances of the finger-vein and fingerprint recognition are improved by using a method based on a local derivative pattern. Second, the accuracy of the finger geometry recognition is greatly increased by combining a Fourier descriptor with principal component analysis. Third, a fuzzy score normalization method is introduced; its performance is better than the conventional Z-score normalization method. Fourth, finger-vein, fingerprint, and finger geometry recognitions are combined by using three support vector machines and a weighted SUM rule. Experimental results showed that the equal error rate of the proposed method was 0.254%, which was lower than those of the other methods.

  14. Multimodal Biometric System Based on the Recognition of Face and Both Irises

    Directory of Open Access Journals (Sweden)

    Yeong Gon Kim

    2012-09-01

    Full Text Available The performance of unimodal biometric systems (based on a single modality such as face or fingerprint has to contend with various problems, such as illumination variation, skin condition and environmental conditions, and device variations. Therefore, multimodal biometric systems have been used to overcome the limitations of unimodal biometrics and provide high accuracy recognition. In this paper, we propose a new multimodal biometric system based on score level fusion of face and both irises' recognition. Our study has the following novel features. First, the device proposed acquires images of the face and both irises simultaneously. The proposed device consists of a face camera, two iris cameras, near-infrared illuminators and cold mirrors. Second, fast and accurate iris detection is based on two circular edge detections, which are accomplished in the iris image on the basis of the size of the iris detected in the face image. Third, the combined accuracy is enhanced by combining each score for the face and both irises using a support vector machine. The experimental results show that the equal error rate for the proposed method is 0.131%, which is lower than that of face or iris recognition and other fusion methods.

  15. Multimodal biometric digital watermarking on immigrant visas for homeland security

    Science.gov (United States)

    Sasi, Sreela; Tamhane, Kirti C.; Rajappa, Mahesh B.

    2004-08-01

    Passengers with immigrant Visa's are a major concern to the International Airports due to the various fraud operations identified. To curb tampering of genuine Visa, the Visa's should contain human identification information. Biometric characteristic is a common and reliable way to authenticate the identity of an individual [1]. A Multimodal Biometric Human Identification System (MBHIS) that integrates iris code, DNA fingerprint, and the passport number on the Visa photograph using digital watermarking scheme is presented. Digital Watermarking technique is well suited for any system requiring high security [2]. Ophthalmologists [3], [4], [5] suggested that iris scan is an accurate and nonintrusive optical fingerprint. DNA sequence can be used as a genetic barcode [6], [7]. While issuing Visa at the US consulates, the DNA sequence isolated from saliva, the iris code and passport number shall be digitally watermarked in the Visa photograph. This information is also recorded in the 'immigrant database'. A 'forward watermarking phase' combines a 2-D DWT transformed digital photograph with the personal identification information. A 'detection phase' extracts the watermarked information from this VISA photograph at the port of entry, from which iris code can be used for identification and DNA biometric for authentication, if an anomaly arises.

  16. On the Quantification of Aging Effects on Biometric Features

    OpenAIRE

    Lanitis , Andreas; Tsapatsoulis , Nicolas

    2010-01-01

    International audience; Biometric templates are often used in intelligent human computer interaction systems that include automated access control and personalization of user interaction. The effectiveness of biometric systems is directly linked with aging that causes modifications on biometric features. For example the long term performance of person identification systems decreases as biometric templates derived from aged subjects may display substantial differences when compared to referen...

  17. Template security analysis of multimodal biometric frameworks based on fingerprint and hand geometry

    Directory of Open Access Journals (Sweden)

    Arvind Selwal

    2016-09-01

    Full Text Available Biometric systems are automatic tools used to provide authentication during various applications of modern computing. In this work, three different design frameworks for multimodal biometric systems based on fingerprint and hand geometry modalities are proposed. An analysis is also presented to diagnose various types of template security issues in the proposed system. Fuzzy analytic hierarchy process (FAHP is applied with five decision parameters on all the designs and framework 1 is found to be better in terms of template data security, templates fusion and computational efficiency. It is noticed that template data security before storage in database is a challenging task. An important observation is that a template may be secured at feature fusion level and an indexing technique may be used to improve the size of secured templates.

  18. MULTIMODAL BIOMETRIC AUTHENTICATION USING PARTICLE SWARM OPTIMIZATION ALGORITHM WITH FINGERPRINT AND IRIS

    Directory of Open Access Journals (Sweden)

    A. Muthukumar

    2012-02-01

    Full Text Available In general, the identification and verification are done by passwords, pin number, etc., which is easily cracked by others. In order to overcome this issue biometrics is a unique tool for authenticate an individual person. Nevertheless, unimodal biometric is suffered due to noise, intra class variations, spoof attacks, non-universality and some other attacks. In order to avoid these attacks, the multimodal biometrics i.e. combining of more modalities is adapted. In a biometric authentication system, the acceptance or rejection of an entity is dependent on the similarity score falling above or below the threshold. Hence this paper has focused on the security of the biometric system, because compromised biometric templates cannot be revoked or reissued and also this paper has proposed a multimodal system based on an evolutionary algorithm, Particle Swarm Optimization that adapts for varying security environments. With these two concerns, this paper had developed a design incorporating adaptability, authenticity and security.

  19. Biometric feature embedding using robust steganography technique

    Science.gov (United States)

    Rashid, Rasber D.; Sellahewa, Harin; Jassim, Sabah A.

    2013-05-01

    This paper is concerned with robust steganographic techniques to hide and communicate biometric data in mobile media objects like images, over open networks. More specifically, the aim is to embed binarised features extracted using discrete wavelet transforms and local binary patterns of face images as a secret message in an image. The need for such techniques can arise in law enforcement, forensics, counter terrorism, internet/mobile banking and border control. What differentiates this problem from normal information hiding techniques is the added requirement that there should be minimal effect on face recognition accuracy. We propose an LSB-Witness embedding technique in which the secret message is already present in the LSB plane but instead of changing the cover image LSB values, the second LSB plane will be changed to stand as a witness/informer to the receiver during message recovery. Although this approach may affect the stego quality, it is eliminating the weakness of traditional LSB schemes that is exploited by steganalysis techniques for LSB, such as PoV and RS steganalysis, to detect the existence of secrete message. Experimental results show that the proposed method is robust against PoV and RS attacks compared to other variants of LSB. We also discussed variants of this approach and determine capacity requirements for embedding face biometric feature vectors while maintain accuracy of face recognition.

  20. Are Haar-like Rectangular Features for Biometric Recognition Reducible?

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2013-01-01

    Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features...... which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal...... and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features...

  1. Unobtrusive behavioral and activity-related multimodal biometrics: The ACTIBIO Authentication concept.

    Science.gov (United States)

    Drosou, A; Ioannidis, D; Moustakas, K; Tzovaras, D

    2011-03-01

    Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, and seat-based anthropometrics. Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. This paper presents the concept of the ACTIBIO project and describes its unobtrusive authentication demonstrator in a real scenario by focusing on the vision-based biometric recognition modalities.

  2. Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images

    Directory of Open Access Journals (Sweden)

    R. Youmaran

    2012-01-01

    Full Text Available This paper develops an approach to measure the information content in a biometric feature representation of iris images. In this context, the biometric feature information is calculated using the relative entropy between the intraclass and interclass feature distributions. The collected data is regularized using a Gaussian model of the feature covariances in order to practically measure the biometric information with limited data samples. An example of this method is shown for iris templates processed using Principal-Component Analysis- (PCA- and Independent-Component Analysis- (ICA- based feature decomposition schemes. From this, the biometric feature information is calculated to be approximately 278 bits for PCA and 288 bits for ICA iris features using Masek's iris recognition scheme. This value approximately matches previous estimates of iris information content.

  3. Deep features for efficient multi-biometric recognition with face and ear images

    Science.gov (United States)

    Omara, Ibrahim; Xiao, Gang; Amrani, Moussa; Yan, Zifei; Zuo, Wangmeng

    2017-07-01

    Recently, multimodal biometric systems have received considerable research interest in many applications especially in the fields of security. Multimodal systems can increase the resistance to spoof attacks, provide more details and flexibility, and lead to better performance and lower error rate. In this paper, we present a multimodal biometric system based on face and ear, and propose how to exploit the extracted deep features from Convolutional Neural Networks (CNNs) on the face and ear images to introduce more powerful discriminative features and robust representation ability for them. First, the deep features for face and ear images are extracted based on VGG-M Net. Second, the extracted deep features are fused by using a traditional concatenation and a Discriminant Correlation Analysis (DCA) algorithm. Third, multiclass support vector machine is adopted for matching and classification. The experimental results show that the proposed multimodal system based on deep features is efficient and achieves a promising recognition rate up to 100 % by using face and ear. In addition, the results indicate that the fusion based on DCA is superior to traditional fusion.

  4. Joint Sparse Representation for Robust Multimodal Biometrics Recognition

    Science.gov (United States)

    2014-01-01

    Biometrics with error term Finger 1 Finger 2 Finger 3 Finger ...Individual Biometrics without error term Finger 1 Finger 2 Finger 3 Finger 4 Iris 1 Iris 2 (a) (b) 20 40 60 80 100 120 140 160 180 200 220 60 65 70...75 80 85 90 95 Rank C um ul at iv e R ec og ni tio n R at e (% ) CMC Curve for Individual Biometrics using SLR Finger 1 Finger 2

  5. Haar-like Rectangular Features for Biometric Recognition

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.; Rashidi, Maryam

    2013-01-01

    Developing a reliable, fast, and robust biometric recognition system is still a challenging task. This is because the inputs to these systems can be noisy, occluded, poorly illuminated, rotated, and of very low-resolutions. This paper proposes a probabilistic classifier using Haar-like features......, which mostly have been used for detection, for biometric recognition. The proposed system has been tested for three different biometrics: ear, iris, and hand vein patterns and it is shown that it is robust against most of the mentioned degradations and it outperforms state-of-the-art systems...

  6. Biometric feature extraction using local fractal auto-correlation

    International Nuclear Information System (INIS)

    Chen Xi; Zhang Jia-Shu

    2014-01-01

    Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)

  7. Unobtrusive Behavioral and Activity-Related Multimodal Biometrics: The ACTIBIO Authentication Concept

    Directory of Open Access Journals (Sweden)

    A. Drosou

    2011-01-01

    Full Text Available Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO is an EU Specific Targeted Research Project (STREP where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, and seat-based anthropometrics. Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. This paper presents the concept of the ACTIBIO project and describes its unobtrusive authentication demonstrator in a real scenario by focusing on the vision-based biometric recognition modalities.

  8. Biometrics Theory, Methods, and Applications

    CERN Document Server

    Boulgouris, N V; Micheli-Tzanakou, Evangelia

    2009-01-01

    An in-depth examination of the cutting edge of biometrics. This book fills a gap in the literature by detailing the recent advances and emerging theories, methods, and applications of biometric systems in a variety of infrastructures. Edited by a panel of experts, it provides comprehensive coverage of:. Multilinear discriminant analysis for biometric signal recognition;. Biometric identity authentication techniques based on neural networks;. Multimodal biometrics and design of classifiers for biometric fusion;. Feature selection and facial aging modeling for face recognition;. Geometrical and

  9. FUSION BASED MULTIMODAL AUTHENTICATION IN BIOMETRICS USING CONTEXT-SENSITIVE EXPONENT ASSOCIATIVE MEMORY MODEL : A NOVEL APPROACH

    OpenAIRE

    P. E. S. N. Krishna Prasad; Pavan Kumar K; M. V. Ramakrishna; B. D. C. N. Prasad

    2013-01-01

    Biometrics is one of the primary key concepts of real application domains such as aadhar card, passport, pan card, etc. In such applications user can provide two to three biometrics patterns like face, finger, palm, signature, iris data, and so on. We considered face and finger patterns for encoding and then also for verification. Using this data we proposed a novel model for authentication in multimodal biometrics often called Context-Sensitive Exponent Associative Memory Mode...

  10. Biometric identification based on feature fusion with PCA and SVM

    Science.gov (United States)

    Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina

    2018-04-01

    Biometric identification is gaining ground compared to traditional identification methods. Many biometric measurements may be used for secure human identification. The most reliable among them is the iris pattern because of its uniqueness, stability, unforgeability and inalterability over time. The approach presented in this paper is a fusion of different feature descriptor methods such as HOG, LIOP, LBP, used for extracting iris texture information. The classifiers obtained through the SVM and PCA methods demonstrate the effectiveness of our system applied to one and both irises. The performances measured are highly accurate and foreshadow a fusion system with a rate of identification approaching 100% on the UPOL database.

  11. Video genre classification using multimodal features

    Science.gov (United States)

    Jin, Sung Ho; Bae, Tae Meon; Choo, Jin Ho; Ro, Yong Man

    2003-12-01

    We propose a video genre classification method using multimodal features. The proposed method is applied for the preprocessing of automatic video summarization or the retrieval and classification of broadcasting video contents. Through a statistical analysis of low-level and middle-level audio-visual features in video, the proposed method can achieve good performance in classifying several broadcasting genres such as cartoon, drama, music video, news, and sports. In this paper, we adopt MPEG-7 audio-visual descriptors as multimodal features of video contents and evaluate the performance of the classification by feeding the features into a decision tree-based classifier which is trained by CART. The experimental results show that the proposed method can recognize several broadcasting video genres with a high accuracy and the classification performance with multimodal features is superior to the one with unimodal features in the genre classification.

  12. Iris Segmentation using Gradient Magnitude and Fourier Descriptor for Multimodal Biometric Authentication System

    Directory of Open Access Journals (Sweden)

    Defiana Sulaeman

    2016-12-01

    Full Text Available Perfectly segmenting the area of the iris is one of the most important steps in iris recognition. There are several problematic areas that affect the accuracy of the iris segmentation step, such as eyelids, eyelashes, glasses, pupil (due to less accurate iris segmentation, motion blur, and lighting and specular reflections. To solve these problems, gradient magnitude and Fourier descriptor are employed to do iris segmentation in the proposed Multimodal Biometric Authentication System (MBAS. This approach showed quite promising results, i.e. an accuracy rate of 97%. The result of the iris recognition system was combined with the result of an open-source fingerprint recognition system to develop a multimodal biometrics authentication system. The results of the fusion between iris and fingerprint authentication were 99% accurate. Data from Multimedia Malaysia University (MMUI and our own prepared database, the SGU-MB-1 dataset, were used to test the accuracy of the proposed system.

  13. Cattle identification based in biometric features of the muzzle

    OpenAIRE

    Monteiro, Marta; Cadavez, Vasco; Monteiro, Fernando C.

    2015-01-01

    Cattle identification has been a serious problem for breeding association. Muzzle pattern or nose print has the same characteristic with the human fingerprint which is the most popular biometric marker. The identification accuracy and the processing time are two key challenges of any cattle identification methodology. This paper presents a robust and fast cattle identification scheme from muzzle images using Speed-up Robust Features matching. The matching refinement technique based on the mat...

  14. A dynamically weighted multi-modal biometric security system

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-09-01

    Full Text Available The face, fingerprint and palmprint feature vectors are automatically extracted and dynamically selected for fusion at the feature-level, toward an improved human identification accuracy. The feature-level has a higher potential accuracy than...

  15. Generating One Biometric Feature from Another: Faces from Fingerprints

    Directory of Open Access Journals (Sweden)

    Seref Sagiroglu

    2010-04-01

    Full Text Available This study presents a new approach based on artificial neural networks for generating one biometric feature (faces from another (only fingerprints. An automatic and intelligent system was designed and developed to analyze the relationships among fingerprints and faces and also to model and to improve the existence of the relationships. The new proposed system is the first study that generates all parts of the face including eyebrows, eyes, nose, mouth, ears and face border from only fingerprints. It is also unique and different from similar studies recently presented in the literature with some superior features. The parameter settings of the system were achieved with the help of Taguchi experimental design technique. The performance and accuracy of the system have been evaluated with 10-fold cross validation technique using qualitative evaluation metrics in addition to the expanded quantitative evaluation metrics. Consequently, the results were presented on the basis of the combination of these objective and subjective metrics for illustrating the qualitative properties of the proposed methods as well as a quantitative evaluation of their performances. Experimental results have shown that one biometric feature can be determined from another. These results have once more indicated that there is a strong relationship between fingerprints and faces.

  16. Generating One Biometric Feature from Another: Faces from Fingerprints

    Science.gov (United States)

    Ozkaya, Necla; Sagiroglu, Seref

    2010-01-01

    This study presents a new approach based on artificial neural networks for generating one biometric feature (faces) from another (only fingerprints). An automatic and intelligent system was designed and developed to analyze the relationships among fingerprints and faces and also to model and to improve the existence of the relationships. The new proposed system is the first study that generates all parts of the face including eyebrows, eyes, nose, mouth, ears and face border from only fingerprints. It is also unique and different from similar studies recently presented in the literature with some superior features. The parameter settings of the system were achieved with the help of Taguchi experimental design technique. The performance and accuracy of the system have been evaluated with 10-fold cross validation technique using qualitative evaluation metrics in addition to the expanded quantitative evaluation metrics. Consequently, the results were presented on the basis of the combination of these objective and subjective metrics for illustrating the qualitative properties of the proposed methods as well as a quantitative evaluation of their performances. Experimental results have shown that one biometric feature can be determined from another. These results have once more indicated that there is a strong relationship between fingerprints and faces. PMID:22399877

  17. Multimodal Feature Learning for Video Captioning

    Directory of Open Access Journals (Sweden)

    Sujin Lee

    2018-01-01

    Full Text Available Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are extracted using convolutional neural networks such as C3D and ResNet, while semantic features are obtained using recurrent neural networks such as LSTM. In addition, our model includes an attention-based caption generation network to generate the correct natural language captions based on the multimodal video feature sequences. Various experiments, conducted with the two large benchmark datasets, Microsoft Video Description (MSVD and Microsoft Research Video-to-Text (MSR-VTT, demonstrate the performance of the proposed model.

  18. The Multimodal Assessment of Adult Attachment Security: Developing the Biometric Attachment Test.

    Science.gov (United States)

    Parra, Federico; Miljkovitch, Raphaële; Persiaux, Gwenaelle; Morales, Michelle; Scherer, Stefan

    2017-04-06

    Attachment theory has been proven essential for mental health, including psychopathology, development, and interpersonal relationships. Validated psychometric instruments to measure attachment abound but suffer from shortcomings common to traditional psychometrics. Recent developments in multimodal fusion and machine learning pave the way for new automated and objective psychometric instruments for adult attachment that combine psychophysiological, linguistic, and behavioral analyses in the assessment of the construct. The aim of this study was to present a new exposure-based, automatic, and objective adult-attachment assessment, the Biometric Attachment Test (BAT), which exposes participants to a short standardized set of visual and music stimuli, whereas their immediate reactions and verbal responses, captured by several computer sense modalities, are automatically analyzed for scoring and classification. We also aimed to empirically validate two of its assumptions: its capacity to measure attachment security and the viability of using themes as placeholders for rotating stimuli. A total of 59 French participants from the general population were assessed using the Adult Attachment Questionnaire (AAQ), the Adult Attachment Projective Picture System (AAP), and the Attachment Multiple Model Interview (AMMI) as ground truth for attachment security. They were then exposed to three different BAT stimuli sets, whereas their faces, voices, heart rate (HR), and electrodermal activity (EDA) were recorded. Psychophysiological features, such as skin-conductance response (SCR) and Bayevsky stress index; behavioral features, such as gaze and facial expressions; as well as linguistic and paralinguistic features, were automatically extracted. An exploratory analysis was conducted using correlation matrices to uncover the features that are most associated with attachment security. A confirmatory analysis was conducted by creating a single composite effects index and by testing it

  19. Design and Implementation of a Multi-Modal Biometric System for Company Access Control

    Directory of Open Access Journals (Sweden)

    Elisabetta Stefani

    2017-05-01

    Full Text Available This paper is about the design, implementation, and deployment of a multi-modal biometric system to grant access to a company structure and to internal zones in the company itself. Face and iris have been chosen as biometric traits. Face is feasible for non-intrusive checking with a minimum cooperation from the subject, while iris supports very accurate recognition procedure at a higher grade of invasivity. The recognition of the face trait is based on the Local Binary Patterns histograms, and the Daughman’s method is implemented for the analysis of the iris data. The recognition process may require either the acquisition of the user’s face only or the serial acquisition of both the user’s face and iris, depending on the confidence level of the decision with respect to the set of security levels and requirements, stated in a formal way in the Service Level Agreement at a negotiation phase. The quality of the decision depends on the setting of proper different thresholds in the decision modules for the two biometric traits. Any time the quality of the decision is not good enough, the system activates proper rules, which ask for new acquisitions (and decisions, possibly with different threshold values, resulting in a system not with a fixed and predefined behaviour, but one which complies with the actual acquisition context. Rules are formalized as deduction rules and grouped together to represent “response behaviors” according to the previous analysis. Therefore, there are different possible working flows, since the actual response of the recognition process depends on the output of the decision making modules that compose the system. Finally, the deployment phase is described, together with the results from the testing, based on the AT&T Face Database and the UBIRIS database.

  20. Feature level fusion of hand and face biometrics

    Science.gov (United States)

    Ross, Arun A.; Govindarajan, Rohin

    2005-03-01

    Multibiometric systems utilize the evidence presented by multiple biometric sources (e.g., face and fingerprint, multiple fingers of a user, multiple matchers, etc.) in order to determine or verify the identity of an individual. Information from multiple sources can be consolidated in several distinct levels, including the feature extraction level, match score level and decision level. While fusion at the match score and decision levels have been extensively studied in the literature, fusion at the feature level is a relatively understudied problem. In this paper we discuss fusion at the feature level in 3 different scenarios: (i) fusion of PCA and LDA coefficients of face; (ii) fusion of LDA coefficients corresponding to the R,G,B channels of a face image; (iii) fusion of face and hand modalities. Preliminary results are encouraging and help in highlighting the pros and cons of performing fusion at this level. The primary motivation of this work is to demonstrate the viability of such a fusion and to underscore the importance of pursuing further research in this direction.

  1. Dual watermarking technique with multiple biometric watermarks

    Indian Academy of Sciences (India)

    affect the visual quality of the original art. On the contrary, removable visible watermarking .... Significant motivation for using biometric features such as face, voice and signature as a watermark is that face and ... These are the major reasons which motivated us to propose multimodal biometric watermarking. When the ...

  2. Biometric recognition via texture features of eye movement trajectories in a visual searching task.

    Science.gov (United States)

    Li, Chunyong; Xue, Jiguo; Quan, Cheng; Yue, Jingwei; Zhang, Chenggang

    2018-01-01

    Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers' temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases.

  3. Comparative study of multimodal biometric recognition by fusion of iris and fingerprint.

    Science.gov (United States)

    Benaliouche, Houda; Touahria, Mohamed

    2014-01-01

    This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

  4. Comparative Study of Multimodal Biometric Recognition by Fusion of Iris and Fingerprint

    Directory of Open Access Journals (Sweden)

    Houda Benaliouche

    2014-01-01

    Full Text Available This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

  5. Comparative Study of Multimodal Biometric Recognition by Fusion of Iris and Fingerprint

    Science.gov (United States)

    Benaliouche, Houda; Touahria, Mohamed

    2014-01-01

    This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results. PMID:24605065

  6. Human body as a set of biometric features identified by means of optoelectronics

    Science.gov (United States)

    Podbielska, Halina; Bauer, Joanna

    2005-09-01

    Human body posses many unique, singular features that are impossible to copy or forge. Nowadays, to establish and to ensure the public security requires specially designed devices and systems. Biometrics is a field of science and technology, exploiting human body characteristics for people recognition. It identifies the most characteristic and unique ones in order to design and construct systems capable to recognize people. In this paper some overview is given, presenting the achievements in biometrics. The verification and identification process is explained, along with the way of evaluation of biometric recognition systems. The most frequently human biometrics used in practice are shortly presented, including fingerprints, facial imaging (including thermal characteristic), hand geometry and iris patterns.

  7. Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal Biometric Fusion Algorithms

    NARCIS (Netherlands)

    N. Poh; T. Bourlai; J. Kittler; L. Allano; F. Alonso-Fernandez; O. Ambekar (Onkar); J. Baker; B. Dorizzi; O. Fatukasi; J. Fierrez; H. Ganster; J. Ortegia-Garcia; D. Maurer; A.A. Salah (Albert Ali); T. Scheidat; C. Vielhauer

    2009-01-01

    htmlabstractAutomatically verifying the identity of a person by means of biometrics (e.g. face and fingerprint) is an important application in our to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are

  8. Improving the Security of Internet Banking Applications by Using Multimodal Biometrics

    Directory of Open Access Journals (Sweden)

    Cătălin Lupu

    2015-03-01

    Full Text Available Online banking applications are used by more and more people all over the world. Most of the banks are providing these services to their customers. The authentication methods varies from the basic user and password to username and a onetime password (OTP generated by a virtual or a physical digipass. The common thing among authentication methods is that the login wepage is provided through a secure channel. Some banks have introduced (especially for testing purposes the authentication using common biometric characteristics, like fingerprint, voice or keystroke recognition. This paper will present some of the most common online banking authentication methods, together with basic biometric characteristics that could be used in these applications. The security in internet banking applications can be improved by using biometrics for the authentication process. Also, the authors have developed an application for authentication of users using fingerprint as the main characteristic, which will be presented at the end of this paper.

  9. Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition.

    Science.gov (United States)

    Gutta, Sandeep; Cheng, Qi

    2016-03-01

    Traditional biometric recognition systems often utilize physiological traits such as fingerprint, face, iris, etc. Recent years have seen a growing interest in electrocardiogram (ECG)-based biometric recognition techniques, especially in the field of clinical medicine. In existing ECG-based biometric recognition methods, feature extraction and classifier design are usually performed separately. In this paper, a multitask learning approach is proposed, in which feature extraction and classifier design are carried out simultaneously. Weights are assigned to the features within the kernel of each task. We decompose the matrix consisting of all the feature weights into sparse and low-rank components. The sparse component determines the features that are relevant to identify each individual, and the low-rank component determines the common feature subspace that is relevant to identify all the subjects. A fast optimization algorithm is developed, which requires only the first-order information. The performance of the proposed approach is demonstrated through experiments using the MIT-BIH Normal Sinus Rhythm database.

  10. Manifold regularized multitask feature learning for multimodality disease classification.

    Science.gov (United States)

    Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

    2015-02-01

    Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis. © 2014 Wiley Periodicals, Inc.

  11. PHROG: A Multimodal Feature for Place Recognition

    Directory of Open Access Journals (Sweden)

    Fabien Bonardi

    2017-05-01

    Full Text Available Long-term place recognition in outdoor environments remains a challenge due to high appearance changes in the environment. The problem becomes even more difficult when the matching between two scenes has to be made with information coming from different visual sources, particularly with different spectral ranges. For instance, an infrared camera is helpful for night vision in combination with a visible camera. In this paper, we emphasize our work on testing usual feature point extractors under both constraints: repeatability across spectral ranges and long-term appearance. We develop a new feature extraction method dedicated to improve the repeatability across spectral ranges. We conduct an evaluation of feature robustness on long-term datasets coming from different imaging sources (optics, sensors size and spectral ranges with a Bag-of-Words approach. The tests we perform demonstrate that our method brings a significant improvement on the image retrieval issue in a visual place recognition context, particularly when there is a need to associate images from various spectral ranges such as infrared and visible: we have evaluated our approach using visible, Near InfraRed (NIR, Short Wavelength InfraRed (SWIR and Long Wavelength InfraRed (LWIR.

  12. Method to assess the temporal persistence of potential biometric features: Application to oculomotor, gait, face and brain structure databases

    Science.gov (United States)

    Nixon, Mark S.; Komogortsev, Oleg V.

    2017-01-01

    We introduce the intraclass correlation coefficient (ICC) to the biometric community as an index of the temporal persistence, or stability, of a single biometric feature. It requires, as input, a feature on an interval or ratio scale, and which is reasonably normally distributed, and it can only be calculated if each subject is tested on 2 or more occasions. For a biometric system, with multiple features available for selection, the ICC can be used to measure the relative stability of each feature. We show, for 14 distinct data sets (1 synthetic, 8 eye-movement-related, 2 gait-related, and 2 face-recognition-related, and one brain-structure-related), that selecting the most stable features, based on the ICC, resulted in the best biometric performance generally. Analyses based on using only the most stable features produced superior Rank-1-Identification Rate (Rank-1-IR) performance in 12 of 14 databases (p = 0.0065, one-tailed), when compared to other sets of features, including the set of all features. For Equal Error Rate (EER), using a subset of only high-ICC features also produced superior performance in 12 of 14 databases (p = 0. 0065, one-tailed). In general, then, for our databases, prescreening potential biometric features, and choosing only highly reliable features yields better performance than choosing lower ICC features or than choosing all features combined. We also determined that, as the ICC of a group of features increases, the median of the genuine similarity score distribution increases and the spread of this distribution decreases. There was no statistically significant similar relationships for the impostor distributions. We believe that the ICC will find many uses in biometric research. In case of the eye movement-driven biometrics, the use of reliable features, as measured by ICC, allowed to us achieve the authentication performance with EER = 2.01%, which was not possible before. PMID:28575030

  13. Feature-based Alignment of Volumetric Multi-modal Images

    Science.gov (United States)

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  14. Feature Selection for Nonstationary Data: Application to Human Recognition Using Medical Biometrics.

    Science.gov (United States)

    Komeili, Majid; Louis, Wael; Armanfard, Narges; Hatzinakos, Dimitrios

    2018-05-01

    Electrocardiogram (ECG) and transient evoked otoacoustic emission (TEOAE) are among the physiological signals that have attracted significant interest in biometric community due to their inherent robustness to replay and falsification attacks. However, they are time-dependent signals and this makes them hard to deal with in across-session human recognition scenario where only one session is available for enrollment. This paper presents a novel feature selection method to address this issue. It is based on an auxiliary dataset with multiple sessions where it selects a subset of features that are more persistent across different sessions. It uses local information in terms of sample margins while enforcing an across-session measure. This makes it a perfect fit for aforementioned biometric recognition problem. Comprehensive experiments on ECG and TEOAE variability due to time lapse and body posture are done. Performance of the proposed method is compared against seven state-of-the-art feature selection algorithms as well as another six approaches in the area of ECG and TEOAE biometric recognition. Experimental results demonstrate that the proposed method performs noticeably better than other algorithms.

  15. Exploiting Multimodal Biometrics in E-Privacy Scheme for Electronic Health Records

    OpenAIRE

    Omotosho, Adebayo; Adegbola, Omotanwa; Adelakin, Barakat; Adelakun, Adeyemi; Emuoyibofarhe, Justice

    2015-01-01

    Existing approaches to protect the privacy of Electronic Health Records are either insufficient for existing medical laws or they are too restrictive in their usage. For example, smart card-based encryption systems require the patient to be always present to authorize access to medical records. Questionnaires were administered by 50 medical practitioners to identify and categorize different Electronic Health Records attributes. The system was implemented using multi biometrics of patients to ...

  16. A novel feature ranking algorithm for biometric recognition with PPG signals.

    Science.gov (United States)

    Reşit Kavsaoğlu, A; Polat, Kemal; Recep Bozkurt, M

    2014-06-01

    This study is intended for describing the application of the Photoplethysmography (PPG) signal and the time domain features acquired from its first and second derivatives for biometric identification. For this purpose, a sum of 40 features has been extracted and a feature-ranking algorithm is proposed. This proposed algorithm calculates the contribution of each feature to biometric recognition and collocates the features, the contribution of which is from great to small. While identifying the contribution of the features, the Euclidean distance and absolute distance formulas are used. The efficiency of the proposed algorithms is demonstrated by the results of the k-NN (k-nearest neighbor) classifier applications of the features. During application, each 15-period-PPG signal belonging to two different durations from each of the thirty healthy subjects were used with a PPG data acquisition card. The first PPG signals recorded from the subjects were evaluated as the 1st configuration; the PPG signals recorded later at a different time as the 2nd configuration and the combination of both were evaluated as the 3rd configuration. When the results were evaluated for the k-NN classifier model created along with the proposed algorithm, an identification of 90.44% for the 1st configuration, 94.44% for the 2nd configuration, and 87.22% for the 3rd configuration has successfully been attained. The obtained results showed that both the proposed algorithm and the biometric identification model based on this developed PPG signal are very promising for contactless recognizing the people with the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Biometrics and Identity Management

    DEFF Research Database (Denmark)

    management. BIOID 2008. The papers are categorized in four classes. These classes represent the 4 working groups of the COST Action 2101. For more information, see http://www.cost2101.org/.   Biometric data quality and multimodal biometric templates, Unsupervised interactive interfaces for multimodal...... security and border control scenarios it is now apparent that the widespread availability of biometrics in everyday life will also spin out an ever increasing number of (private) applications in other domains. Crucial to this vision is the management of the user's identity, which does not only imply...... biometrics, Biometric attacks and countermeasures, Standards and privacy issues for biometrics in identity documents and smart cards. BIOID 2008 is an initiative of the COST Action 2101 on Biometrics for Identity Documents and Smart Cards. It is supported by the EU Framework 7 Programme. Other sponsors...

  18. BIOMETRIC CRYPTOGRAPHY AND NETWORK AUTHENTICATION

    Directory of Open Access Journals (Sweden)

    Tonimir Kišasondi

    2007-06-01

    Full Text Available In this paper we will present some schemes for strengthening network authentification over insecure channels with biometric concepts or how to securely transfer or use biometric characteristics as cryptographic keys. We will show why some current authentification schemes are insufficient and we will present our concepts of biometric hashes and authentification that rely on unimodal and multimodal biometrics. Our concept can be applied on any biometric authentification scheme and is universal for all systems.

  19. Optimization of an individual re-identification modeling process using biometric features

    Energy Technology Data Exchange (ETDEWEB)

    Heredia-Langner, Alejandro; Amidan, Brett G.; Matzner, Shari; Jarman, Kristin H.

    2014-09-24

    We present results from the optimization of a re-identification process using two sets of biometric data obtained from the Civilian American and European Surface Anthropometry Resource Project (CAESAR) database. The datasets contain real measurements of features for 2378 individuals in a standing (43 features) and seated (16 features) position. A genetic algorithm (GA) was used to search a large combinatorial space where different features are available between the probe (seated) and gallery (standing) datasets. Results show that optimized model predictions obtained using less than half of the 43 gallery features and data from roughly 16% of the individuals available produce better re-identification rates than two other approaches that use all the information available.

  20. Multimodal Image Alignment via Linear Mapping between Feature Modalities.

    Science.gov (United States)

    Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James

    2017-01-01

    We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.

  1. Feature Level Two -Dimensional Arrays Based Fusion in the Personal Authentication system using Physiological Biometric traits

    Directory of Open Access Journals (Sweden)

    Jerusalin Carol .J

    Full Text Available ABSTRACT The fingerprint, knuckle print and the retina are used to authenticate a person accurately because of the permanence in the features. These three biometric traits are fused for better security. The fingerprint and knuckle print images are pre-processed by morphological techniques and the features are extracted from the normalized image using gabor filter. The retinal image is converted to gray image and pre-processing is done using top hat and bottom hat filtering. Blood vessels are segmented and the features are extracted by locating the optic disk as the centre point. The extracted features from the fingerprint, knuckle print and the retina are fused together as one template and stored in the data base for authentication purpose, thus reducing the space and time complexity.

  2. Biometric identification of cardiosynchronous waveforms utilizing person specific continuous and discrete wavelet transform features.

    Science.gov (United States)

    Bhagavatula, Chandrasekhar; Venugopalan, Shreyas; Blue, Rebecca; Friedman, Robert; Griofa, Marc O; Savvides, Marios; Kumar, B V K Vijaya

    2012-01-01

    In this paper we explore how a Radio Frequency Impedance Interrogation (RFII) signal may be used as a biometric feature. This could allow the identification of subjects in operational and potentially hostile environments. Features extracted from the continuous and discrete wavelet decompositions of the signal are investigated for biometric identification. In the former case, the most discriminative features in the wavelet space were extracted using a Fisher ratio metric. Comparisons in the wavelet space were done using the Euclidean distance measure. In the latter case, the signal was decomposed at various levels using different wavelet bases, in order to extract both low frequency and high frequency components. Comparisons at each decomposition level were performed using the same distance measure as before. The data set used consists of four subjects, each with a 15 minute RFII recording. The various data samples for our experiments, corresponding to a single heart beat duration, were extracted from these recordings. We achieve identification rates of up to 99% using the CWT approach and rates of up to 100% using the DWT approach. While the small size of the dataset limits the interpretation of these results, further work with larger datasets is expected to develop better algorithms for subject identification.

  3. Automatic lip reading by using multimodal visual features

    Science.gov (United States)

    Takahashi, Shohei; Ohya, Jun

    2013-12-01

    Since long time ago, speech recognition has been researched, though it does not work well in noisy places such as in the car or in the train. In addition, people with hearing-impaired or difficulties in hearing cannot receive benefits from speech recognition. To recognize the speech automatically, visual information is also important. People understand speeches from not only audio information, but also visual information such as temporal changes in the lip shape. A vision based speech recognition method could work well in noisy places, and could be useful also for people with hearing disabilities. In this paper, we propose an automatic lip-reading method for recognizing the speech by using multimodal visual information without using any audio information such as speech recognition. First, the ASM (Active Shape Model) is used to track and detect the face and lip in a video sequence. Second, the shape, optical flow and spatial frequencies of the lip features are extracted from the lip detected by ASM. Next, the extracted multimodal features are ordered chronologically so that Support Vector Machine is performed in order to learn and classify the spoken words. Experiments for classifying several words show promising results of this proposed method.

  4. Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology

    Energy Technology Data Exchange (ETDEWEB)

    Hammond, Tracy [Texas A& M University, College Station; Tourassi, Georgia [ORNL; Yoon, Hong-Jun [ORNL; Alamudun, Folami T. [ORNL

    2017-07-01

    In this study, we present a novel application of sketch gesture recognition on eye-movement for biometric identification and estimating task expertise. The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) and 10 readers (three board certified radiologists and seven radiology residents), formed the corpus for this study. Sketch gesture recognition techniques were employed to extract geometric and gesture-based features from saccadic eye-movements. Our results show that saccadic eye-movement, characterized using sketch-based features, result in more accurate models for predicting individual identity and level of expertise than more traditional eye-tracking features.

  5. Modality prediction of biomedical literature images using multimodal feature representation

    Directory of Open Access Journals (Sweden)

    Pelka, Obioma

    2016-08-01

    Full Text Available This paper presents the modelling approaches performed to automatically predict the modality of images found in biomedical literature. Various state-of-the-art visual features such as Bag-of-Keypoints computed with dense SIFT descriptors, texture features and Joint Composite Descriptors were used for visual image representation. Text representation was obtained by vector quantisation on a Bag-of-Words dictionary generated using attribute importance derived from a χ-test. Computing the principal components separately on each feature, dimension reduction as well as computational load reduction was achieved. Various multiple feature fusions were adopted to supplement visual image information with corresponding text information. The improvement obtained when using multimodal features vs. visual or text features was detected, analysed and evaluated. Random Forest models with 100 to 500 deep trees grown by resampling, a multi class linear kernel SVM with C=0.05 and a late fusion of the two classifiers were used for modality prediction. A Random Forest classifier achieved a higher accuracy and computed Bag-of-Keypoints with dense SIFT descriptors proved to be a better approach than with Lowe SIFT.

  6. Advances in biometrics for secure human authentication and recognition

    CERN Document Server

    Kisku, Dakshina Ranjan; Sing, Jamuna Kanta

    2013-01-01

    GENERAL BIOMETRICSSecurity and Reliability Assessment for Biometric Systems; Gayatri MirajkarReview of Human Recognition Based on Retinal Images; Amin DehghaniADVANCED TOPICS IN BIOMETRICSVisual Speech as Behavioral Biometric; Preety Singh, Vijay Laxmi, and Manoj Singh GaurHuman Gait Signature for Biometric Authentication; Vijay JohnHand-Based Biometric for Personal Identification Using Correlation Filter Classifier; Mohammed Saigaa , Abdallah Meraoumia , Salim Chitroub, and Ahmed BouridaneOn Deciding the Dynamic Periocular Boundary for Human Recognition; Sambit Bakshi , Pankaj Kumar Sa, and Banshidhar MajhiRetention of Electrocardiogram Features Insignificantly Devalorized as an Effect of Watermarking for a Multimodal Biometric Authentication System; Nilanjan Dey, Bijurika Nandi, Poulami Das, Achintya Das, and Sheli Sinha ChaudhuriFacial Feature Point Extraction for Object Identification Using Discrete Contourlet Transform and Principal Component Analysis; N. G. Chitaliya and A. I. TrivediCASE STUDIES AND LA...

  7. Performance Evaluation of Multimodal Multifeature Authentication System Using KNN Classification

    Directory of Open Access Journals (Sweden)

    Gayathri Rajagopal

    2015-01-01

    Full Text Available This research proposes a multimodal multifeature biometric system for human recognition using two traits, that is, palmprint and iris. The purpose of this research is to analyse integration of multimodal and multifeature biometric system using feature level fusion to achieve better performance. The main aim of the proposed system is to increase the recognition accuracy using feature level fusion. The features at the feature level fusion are raw biometric data which contains rich information when compared to decision and matching score level fusion. Hence information fused at the feature level is expected to obtain improved recognition accuracy. However, information fused at feature level has the problem of curse in dimensionality; here PCA (principal component analysis is used to diminish the dimensionality of the feature sets as they are high dimensional. The proposed multimodal results were compared with other multimodal and monomodal approaches. Out of these comparisons, the multimodal multifeature palmprint iris fusion offers significant improvements in the accuracy of the suggested multimodal biometric system. The proposed algorithm is tested using created virtual multimodal database using UPOL iris database and PolyU palmprint database.

  8. Different Approaches for Face Authentication as Part of a Multimodal Biometrics System

    Directory of Open Access Journals (Sweden)

    Jaromir Tovarek

    2018-01-01

    Full Text Available This paper describes different approaches for the face authentication from the features and classification abilities point of view. Authors compare two types of features - Histogram of Oriented Gradients (HOG and Local Binary Patterns (LBP including their combination. These parameters are classified using Multilayer Neural Network (MLNN and Support Vector Machines (SVM. Face authentication consists of several steps. The first step contains Viola-Jones algorithm for face detection. Authors resize the detected face for a fixed vector and afterwards, it is converted into grayscale. Next, feature extraction with a simple Min-Max normalization is applied. Obtained parameters are evaluated by classifiers and for each detected face, authors get posterior probability as the output of the classifier. Different approaches for face authentication are compared with each other using False Acceptance Rate (FAR, False Rejection Rate (FRR, Equal Error Rate (EER, Receiver Operating Characteristic (ROC and Detection Error Tradeoff (DET curves. The results are verified with AR Face Database and elaborated in a feature extraction and classifier design point of view. Best results were achieved by HOG feature for SVM classifier. Detailed results are listed in the text below.

  9. Hand Biometric Recognition Based on Fused Hand Geometry and Vascular Patterns

    Science.gov (United States)

    Park, GiTae; Kim, Soowon

    2013-01-01

    A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%. PMID:23449119

  10. Hand biometric recognition based on fused hand geometry and vascular patterns.

    Science.gov (United States)

    Park, GiTae; Kim, Soowon

    2013-02-28

    A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%.

  11. Using medical history embedded in biometrics medical card for user identity authentication: privacy preserving authentication model by features matching.

    Science.gov (United States)

    Fong, Simon; Zhuang, Yan

    2012-01-01

    Many forms of biometrics have been proposed and studied for biometrics authentication. Recently researchers are looking into longitudinal pattern matching that based on more than just a singular biometrics; data from user's activities are used to characterise the identity of a user. In this paper we advocate a novel type of authentication by using a user's medical history which can be electronically stored in a biometric security card. This is a sequel paper from our previous work about defining abstract format of medical data to be queried and tested upon authentication. The challenge to overcome is preserving the user's privacy by choosing only the useful features from the medical data for use in authentication. The features should contain less sensitive elements and they are implicitly related to the target illness. Therefore exchanging questions and answers about a few carefully chosen features in an open channel would not easily or directly expose the illness, but yet it can verify by inference whether the user has a record of it stored in his smart card. The design of a privacy preserving model by backward inference is introduced in this paper. Some live medical data are used in experiments for validation and demonstration.

  12. Using Medical History Embedded in Biometrics Medical Card for User Identity Authentication: Privacy Preserving Authentication Model by Features Matching

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2012-01-01

    Full Text Available Many forms of biometrics have been proposed and studied for biometrics authentication. Recently researchers are looking into longitudinal pattern matching that based on more than just a singular biometrics; data from user’s activities are used to characterise the identity of a user. In this paper we advocate a novel type of authentication by using a user’s medical history which can be electronically stored in a biometric security card. This is a sequel paper from our previous work about defining abstract format of medical data to be queried and tested upon authentication. The challenge to overcome is preserving the user’s privacy by choosing only the useful features from the medical data for use in authentication. The features should contain less sensitive elements and they are implicitly related to the target illness. Therefore exchanging questions and answers about a few carefully chosen features in an open channel would not easily or directly expose the illness, but yet it can verify by inference whether the user has a record of it stored in his smart card. The design of a privacy preserving model by backward inference is introduced in this paper. Some live medical data are used in experiments for validation and demonstration.

  13. An enhanced PSO-DEFS based feature selection with biometric authentication for identification of diabetic retinopathy

    Directory of Open Access Journals (Sweden)

    Umarani Balakrishnan

    2016-11-01

    Full Text Available Recently, automatic diagnosis of diabetic retinopathy (DR from the retinal image is the most significant research topic in the medical applications. Diabetic macular edema (DME is the major reason for the loss of vision in patients suffering from DR. Early identification of the DR enables to prevent the vision loss and encourage diabetic control activities. Many techniques are developed to diagnose the DR. The major drawbacks of the existing techniques are low accuracy and high time complexity. To overcome these issues, this paper proposes an enhanced particle swarm optimization-differential evolution feature selection (PSO-DEFS based feature selection approach with biometric authentication for the identification of DR. Initially, a hybrid median filter (HMF is used for pre-processing the input images. Then, the pre-processed images are embedded with each other by using least significant bit (LSB for authentication purpose. Simultaneously, the image features are extracted using convoluted local tetra pattern (CLTrP and Tamura features. Feature selection is performed using PSO-DEFS and PSO-gravitational search algorithm (PSO-GSA to reduce time complexity. Based on some performance metrics, the PSO-DEFS is chosen as a better choice for feature selection. The feature selection is performed based on the fitness value. A multi-relevance vector machine (M-RVM is introduced to classify the 13 normal and 62 abnormal images among 75 images from 60 patients. Finally, the DR patients are further classified by M-RVM. The experimental results exhibit that the proposed approach achieves better accuracy, sensitivity, and specificity than the existing techniques.

  14. Transformation of hand-shape features for a biometric identification approach.

    Science.gov (United States)

    Travieso, Carlos M; Briceño, Juan Carlos; Alonso, Jesús B

    2012-01-01

    The present work presents a biometric identification system for hand shape identification. The different contours have been coded based on angular descriptions forming a Markov chain descriptor. Discrete Hidden Markov Models (DHMM), each representing a target identification class, have been trained with such chains. Features have been calculated from a kernel based on the HMM parameter descriptors. Finally, supervised Support Vector Machines were used to classify parameters from the DHMM kernel. First, the system was modelled using 60 users to tune the DHMM and DHMM_kernel+SVM configuration parameters and finally, the system was checked with the whole database (GPDS database, 144 users with 10 samples per class). Our experiments have obtained similar results in both cases, demonstrating a scalable, stable and robust system. Our experiments have achieved an upper success rate of 99.87% for the GPDS database using three hand samples per class in training mode, and seven hand samples in test mode. Secondly, the authors have verified their algorithms using another independent and public database (the UST database). Our approach has reached 100% and 99.92% success for right and left hand, respectively; showing the robustness and independence of our algorithms. This success was found using as features the transformation of 100 points hand shape with our DHMM kernel, and as classifier Support Vector Machines with linear separating functions, with similar success.

  15. Transformation of Hand-Shape Features for a Biometric Identification Approach

    Directory of Open Access Journals (Sweden)

    Jesús B. Alonso

    2012-01-01

    Full Text Available The present work presents a biometric identification system for hand shape identification. The different contours have been coded based on angular descriptions forming a Markov chain descriptor. Discrete Hidden Markov Models (DHMM, each representing a target identification class, have been trained with such chains. Features have been calculated from a kernel based on the HMM parameter descriptors. Finally, supervised Support Vector Machines were used to classify parameters from the DHMM kernel. First, the system was modelled using 60 users to tune the DHMM and DHMM_kernel+SVM configuration parameters and finally, the system was checked with the whole database (GPDS database, 144 users with 10 samples per class. Our experiments have obtained similar results in both cases, demonstrating a scalable, stable and robust system. Our experiments have achieved an upper success rate of 99.87% for the GPDS database using three hand samples per class in training mode, and seven hand samples in test mode. Secondly, the authors have verified their algorithms using another independent and public database (the UST database. Our approach has reached 100% and 99.92% success for right and left hand, respectively; showing the robustness and independence of our algorithms. This success was found using as features the transformation of 100 points hand shape with our DHMM kernel, and as classifier Support Vector Machines with linear separating functions, with similar success.

  16. A Robust Multimodal Bio metric Authentication Scheme with Voice and Face Recognition

    International Nuclear Information System (INIS)

    Kasban, H.

    2017-01-01

    This paper proposes a multimodal biometric scheme for human authentication based on fusion of voice and face recognition. For voice recognition, three categories of features (statistical coefficients, cepstral coefficients and voice timbre) are used and compared. The voice identification modality is carried out using Gaussian Mixture Model (GMM). For face recognition, three recognition methods (Eigenface, Linear Discriminate Analysis (LDA), and Gabor filter) are used and compared. The combination of voice and face biometrics systems into a single multimodal biometrics system is performed using features fusion and scores fusion. This study shows that the best results are obtained using all the features (cepstral coefficients, statistical coefficients and voice timbre features) for voice recognition, LDA face recognition method and scores fusion for the multimodal biometrics system

  17. Effect of sowing date on biometrical features of Hamburg parsley plants

    Directory of Open Access Journals (Sweden)

    Robert Gruszecki

    2013-04-01

    Full Text Available The aim of this study was to determine the relationship between sowing date and the biometrics features of the roots and leaves of parsley. Seeds of parsley cultivars ‘Berlińska PNE’ and ‘Cukrowa’ were sown in 5 times in 2004 year: 5 July, 25 August, 5 and 15 September, 17 November and 12 April 2005. Plants were harvested then the average root diameter was greater than 20 mm. Due to harvest time dependence of the size of the root, was no effect of sowing date on the diameter and the weight of gained parsley roots. Shorter roots and the lower coefficient of shape produced plants that sprouted before winter (5 July, 25 August, 5 and 15 September. The highest number of leaves produced by plants sowing on 5 July and 17 November, and the lowest – by plants sowing on 25 August and 12 April. The lowest length of leaves were found in plants obtained from sowing on 5 July (20.8 cm, it was more than twice shorter than in plants from different dates of sowing. The largest weight of leaves had the plants from sowing on 5 and 15 September or 17 November. Those plants are also characterized by a smaller root/shoot weight ratio. Tested cultivars differ in the length and coefficient of shape of the root and root/shoot weight ratio.

  18. New Finger Biometric Method Using Near Infrared Imaging

    Science.gov (United States)

    Lee, Eui Chul; Jung, Hyunwoo; Kim, Daeyeoul

    2011-01-01

    In this paper, we propose a new finger biometric method. Infrared finger images are first captured, and then feature extraction is performed using a modified Gaussian high-pass filter through binarization, local binary pattern (LBP), and local derivative pattern (LDP) methods. Infrared finger images include the multimodal features of finger veins and finger geometries. Instead of extracting each feature using different methods, the modified Gaussian high-pass filter is fully convolved. Therefore, the extracted binary patterns of finger images include the multimodal features of veins and finger geometries. Experimental results show that the proposed method has an error rate of 0.13%. PMID:22163741

  19. The Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Sense

    Science.gov (United States)

    Quek, Francis

    2004-12-01

    The catchment feature model addresses two questions in the field of multimodal interaction: how we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. We argue from a detailed literature review that gestural research has clustered around manipulative and semaphoric use of the hands, motivate the catchment feature model psycholinguistic research, and present the model. In contrast to "whole gesture" recognition, the catchment feature model applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. We present our experimental framework for catchment feature-based research, cite three concrete examples of catchment features, and propose new directions of multimodal research based on the model.

  20. The Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Sense

    Directory of Open Access Journals (Sweden)

    Francis Quek

    2004-09-01

    Full Text Available The catchment feature model addresses two questions in the field of multimodal interaction: how we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. We argue from a detailed literature review that gestural research has clustered around manipulative and semaphoric use of the hands, motivate the catchment feature model psycholinguistic research, and present the model. In contrast to “whole gesture” recognition, the catchment feature model applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. We present our experimental framework for catchment feature-based research, cite three concrete examples of catchment features, and propose new directions of multimodal research based on the model.

  1. The biometric recognition on contactless multi-spectrum finger images

    Science.gov (United States)

    Kang, Wenxiong; Chen, Xiaopeng; Wu, Qiuxia

    2015-01-01

    This paper presents a novel multimodal biometric system based on contactless multi-spectrum finger images, which aims to deal with the limitations of unimodal biometrics. The chief merits of the system are the richness of the permissible texture and the ease of data access. We constructed a multi-spectrum instrument to simultaneously acquire three different types of biometrics from a finger: contactless fingerprint, finger vein, and knuckleprint. On the basis of the samples with these characteristics, a moderate database was built for the evaluation of our system. Considering the real-time requirements and the respective characteristics of the three biometrics, the block local binary patterns algorithm was used to extract features and match for the fingerprints and finger veins, while the Oriented FAST and Rotated BRIEF algorithm was applied for knuckleprints. Finally, score-level fusion was performed on the matching results from the aforementioned three types of biometrics. The experiments showed that our proposed multimodal biometric recognition system achieves an equal error rate of 0.109%, which is 88.9%, 94.6%, and 89.7% lower than the individual fingerprint, knuckleprint, and finger vein recognitions, respectively. Nevertheless, our proposed system also satisfies the real-time requirements of the applications.

  2. The Distinct Biometric Features of High Myopia Compared to Moderate Myopia.

    Science.gov (United States)

    Chung, Hye Jin; Park, Chan Kee

    2016-12-01

    To evaluate changes in biometric parameters in myopic eyes. 412 eyes of 412 young myopic patients underwent ophthalmic examinations including assessments of refractive error, axial length (AL), anterior chamber depth (ACD), and central corneal thickness (CCT). By using spectral domain optical coherence tomography (SD-OCT), peripapillary retinal nerve fiber layer (pRNFL) thickness was measured. Subjects were divided into two groups: a moderate-myope group (-6 diopters (D) or more) and a high-myope group (less than -6 D). The relationships among ocular biometric parameters including pRNFL thickness, AL, ACD, and CCT were calculated for each group. In the moderate-myopia group, the anterior chamber deepened as AL increased (Pearson's coefficient = 0.346, p biometric parameter in highly myopic eyes should consider these differences.

  3. On Applicability of Tunable Filter Bank Based Feature for Ear Biometrics: A Study from Constrained to Unconstrained.

    Science.gov (United States)

    Chowdhury, Debbrota Paul; Bakshi, Sambit; Guo, Guodong; Sa, Pankaj Kumar

    2017-11-27

    In this paper, an overall framework has been presented for person verification using ear biometric which uses tunable filter bank as local feature extractor. The tunable filter bank, based on a half-band polynomial of 14th order, extracts distinct features from ear images maintaining its frequency selectivity property. To advocate the applicability of tunable filter bank on ear biometrics, recognition test has been performed on available constrained databases like AMI, WPUT, IITD and unconstrained database like UERC. Experiments have been conducted applying tunable filter based feature extractor on subparts of the ear. Empirical experiments have been conducted with four and six subdivisions of the ear image. Analyzing the experimental results, it has been found that tunable filter moderately succeeds to distinguish ear features at par with the state-of-the-art features used for ear recognition. Accuracies of 70.58%, 67.01%, 81.98%, and 57.75% have been achieved on AMI, WPUT, IITD, and UERC databases through considering Canberra Distance as underlying measure of separation. The performances indicate that tunable filter is a candidate for recognizing human from ear images.

  4. Comparing of athletic performance and biometric features of selected teenagers based on the specific talent identification pattern of Karate with elite athletes

    OpenAIRE

    seyed Ehsan Naghibi; Mehrdad Anbarian; Mohammad Reza Mahmoodkhani

    2017-01-01

    Objective: The aim of this study was to comparing the athletic performance and biometric features in elite karate players teenagers with a specific talent identification pattern of  karate in a professional gyms in Iran. Methods: Subjects available for sampling were divided into two groups teenagers karate athletes elite (n=19) and members developmental center and the Club Championship (n=19) for assessing the biometric data of the sport performance tests respectively. Shapiro-Wilk te...

  5. Multimodality

    DEFF Research Database (Denmark)

    Buhl, Mie

    2010-01-01

    In this paper, I address an ongoing discussion in Danish E-learning research about how to take advantage of the fact that digital media facilitate other communication forms than text, so-called ‘multimodal' communication, which should not be confused with the term ‘multimedia'. While multimedia...... on their teaching and learning situations. The choices they make involve e-learning resources like videos, social platforms and mobile devices, not just as digital artefacts we interact with, but the entire practice of using digital media. In a life-long learning perspective, multimodality is potentially very...

  6. Effects of the feeding system and breed on the growth performance, biometric features, and ruminal development of feedlot goat kids

    Directory of Open Access Journals (Sweden)

    Pedro Paulo Sobolow de Souza

    2016-08-01

    Full Text Available The objective of this experiment was to evaluate the effect of 2 feeding systems and 5 breeding groups on the growth performance, biometric features, and stomach morphology of feedlot goat kids. The experiment utilized gender as a randomized blocking factor in a 5 × 2 factorial scheme. The study goats were from the Alpine, Anglo-Nubian, 1/2 Boer x Alpine, 3/4 Boer x Alpine, and 7/8 Boer x Alpine breeds. Half of the goats were fed an experimental diet, whereas the other half were given the same diet supplemented with 1.5 L milk daily. The kids were slaughtered after they attained 30 kg body weight. The 1/2 Boer x Alpine goats showed superior growth performance because they exhibiting considerable heterosis. These animals are especially easy to use given that there is no need to maintain cross-bred females (½ Boer x Alpine e ¾ Boer x Alpine in the flock. Using milk in the feed the animals does not adversely affect growth performance or biometric features. Moreover, it helps to reduce the total weight of the stomach and leads to a 51.39% savings on feed. Dietary supplementation of milk in goat feed is recommended so long as there is excess milk available on the property.

  7. Signal and image processing for biometrics

    CERN Document Server

    Proença, Hugo; Du, Eliza

    2014-01-01

    This volume offers a guide to the state of the art in the fast evolving field of biometric recognition to newcomers and experienced practitioners. It is focused on the emerging strategies to perform biometric recognition under uncontrolled data acquisition conditions. The mainstream research work in this field is presented in an organized manner, so the reader can easily follow the trends that best suits her/his interests in this growing field. The book chapters cover the recent advances in less controlled / covert data acquisition frameworks, segmentation of poor quality biometric data, biometric data quality assessment, normalization of poor quality biometric data. contactless biometric recognition strategies, biometric recognition robustness, data resolution, illumination, distance, pose, motion, occlusions, multispectral biometric recognition, multimodal biometrics, fusion at different levels, high confidence automatic surveillance.

  8. Learning in data-limited multimodal scenarios: Scandent decision forests and tree-based features.

    Science.gov (United States)

    Hor, Soheil; Moradi, Mehdi

    2016-12-01

    Incomplete and inconsistent datasets often pose difficulties in multimodal studies. We introduce the concept of scandent decision trees to tackle these difficulties. Scandent trees are decision trees that optimally mimic the partitioning of the data determined by another decision tree, and crucially, use only a subset of the feature set. We show how scandent trees can be used to enhance the performance of decision forests trained on a small number of multimodal samples when we have access to larger datasets with vastly incomplete feature sets. Additionally, we introduce the concept of tree-based feature transforms in the decision forest paradigm. When combined with scandent trees, the tree-based feature transforms enable us to train a classifier on a rich multimodal dataset, and use it to classify samples with only a subset of features of the training data. Using this methodology, we build a model trained on MRI and PET images of the ADNI dataset, and then test it on cases with only MRI data. We show that this is significantly more effective in staging of cognitive impairments compared to a similar decision forest model trained and tested on MRI only, or one that uses other kinds of feature transform applied to the MRI data. Copyright © 2016. Published by Elsevier B.V.

  9. Multimodal Feature Integration in the Angular Gyrus during Episodic and Semantic Retrieval

    Science.gov (United States)

    Bonnici, Heidi M.; Richter, Franziska R.; Yazar, Yasemin

    2016-01-01

    Much evidence from distinct lines of investigation indicates the involvement of angular gyrus (AnG) in the retrieval of both episodic and semantic information, but the region's precise function and whether that function differs across episodic and semantic retrieval have yet to be determined. We used univariate and multivariate fMRI analysis methods to examine the role of AnG in multimodal feature integration during episodic and semantic retrieval. Human participants completed episodic and semantic memory tasks involving unimodal (auditory or visual) and multimodal (audio-visual) stimuli. Univariate analyses revealed the recruitment of functionally distinct AnG subregions during the retrieval of episodic and semantic information. Consistent with a role in multimodal feature integration during episodic retrieval, significantly greater AnG activity was observed during retrieval of integrated multimodal episodic memories compared with unimodal episodic memories. Multivariate classification analyses revealed that individual multimodal episodic memories could be differentiated in AnG, with classification accuracy tracking the vividness of participants' reported recollections, whereas distinct unimodal memories were represented in sensory association areas only. In contrast to episodic retrieval, AnG was engaged to a statistically equivalent degree during retrieval of unimodal and multimodal semantic memories, suggesting a distinct role for AnG during semantic retrieval. Modality-specific sensory association areas exhibited corresponding activity during both episodic and semantic retrieval, which mirrored the functional specialization of these regions during perception. The results offer new insights into the integrative processes subserved by AnG and its contribution to our subjective experience of remembering. SIGNIFICANCE STATEMENT Using univariate and multivariate fMRI analyses, we provide evidence that functionally distinct subregions of angular gyrus (An

  10. Multimodal Feature Integration in the Angular Gyrus during Episodic and Semantic Retrieval.

    Science.gov (United States)

    Bonnici, Heidi M; Richter, Franziska R; Yazar, Yasemin; Simons, Jon S

    2016-05-18

    Much evidence from distinct lines of investigation indicates the involvement of angular gyrus (AnG) in the retrieval of both episodic and semantic information, but the region's precise function and whether that function differs across episodic and semantic retrieval have yet to be determined. We used univariate and multivariate fMRI analysis methods to examine the role of AnG in multimodal feature integration during episodic and semantic retrieval. Human participants completed episodic and semantic memory tasks involving unimodal (auditory or visual) and multimodal (audio-visual) stimuli. Univariate analyses revealed the recruitment of functionally distinct AnG subregions during the retrieval of episodic and semantic information. Consistent with a role in multimodal feature integration during episodic retrieval, significantly greater AnG activity was observed during retrieval of integrated multimodal episodic memories compared with unimodal episodic memories. Multivariate classification analyses revealed that individual multimodal episodic memories could be differentiated in AnG, with classification accuracy tracking the vividness of participants' reported recollections, whereas distinct unimodal memories were represented in sensory association areas only. In contrast to episodic retrieval, AnG was engaged to a statistically equivalent degree during retrieval of unimodal and multimodal semantic memories, suggesting a distinct role for AnG during semantic retrieval. Modality-specific sensory association areas exhibited corresponding activity during both episodic and semantic retrieval, which mirrored the functional specialization of these regions during perception. The results offer new insights into the integrative processes subserved by AnG and its contribution to our subjective experience of remembering. Using univariate and multivariate fMRI analyses, we provide evidence that functionally distinct subregions of angular gyrus (AnG) contribute to the retrieval of

  11. Multimodal Ultrawide-Field Imaging Features in Waardenburg Syndrome.

    Science.gov (United States)

    Choudhry, Netan; Rao, Rajesh C

    2015-06-01

    A 45-year-old woman was referred for bilateral irregular fundus pigmentation. Dilated fundus examination revealed irregular hypopigmentation posterior to the equator in both eyes, confirmed by fundus autofluorescence. A thickened choroid was seen on enhanced-depth imaging spectral-domain optical coherence tomography (EDI SD-OCT). Systemic evaluation revealed sensorineural deafness, telecanthus, and a white forelock. Further investigation revealed a first-degree relative with Waardenburg syndrome. Waardenburg syndrome is characterized by a group of features including telecanthus, a broad nasal root, synophrys of the eyebrows, piedbaldism, heterochromia irides, and deafness. Choroidal hypopigmentation is a unique feature that can be visualized with ultrawide-field fundus autofluorescence. The choroid may also be thickened and its thickness measured with EDI SD-OCT. Copyright 2015, SLACK Incorporated.

  12. Manifold regularized multi-task feature selection for multi-modality classification in Alzheimer's disease.

    Science.gov (United States)

    Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

    2013-01-01

    Accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method.

  13. Multimodality

    DEFF Research Database (Denmark)

    Buhl, Mie

    In this paper, I address an ongoing discussion in Danish E-learning research about how to take advantage of the fact that digital media facilitate other communication forms than text, so-called ‘multimodal’ communication, which should not be confused with the term ‘multimedia’. While multimedia...... and learning situations. The choices they make involve E-learning resources like videos, social platforms and mobile devices, not just as digital artefacts we interact with, but the entire practice of using digital media. In a life-long learning perspective, multimodality is potentially very useful...

  14. Evolutionary Algorithms Application Analysis in Biometric Systems

    OpenAIRE

    N. Goranin; A. Cenys

    2010-01-01

    Wide usage of biometric information for person identity verification purposes, terrorist acts prevention measures and authenticationprocess simplification in computer systems has raised significant attention to reliability and efficiency of biometricsystems. Modern biometric systems still face many reliability and efficiency related issues such as reference databasesearch speed, errors while recognizing of biometric information or automating biometric feature extraction. Current scientificinv...

  15. Facial expression recognition in the wild based on multimodal texture features

    Science.gov (United States)

    Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

    2016-11-01

    Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

  16. Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

    Science.gov (United States)

    Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

    2018-02-05

    Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Issues in Biometric Security

    African Journals Online (AJOL)

    Ogechukwu Iloanusi

    Human recognition is required for certain ... automated systems is that some can be stolen, passwords and PIN ... WORKS. A biometric system can be viewed as a simple diagram in figure 1. ... Feature extraction is done with the help of some.

  18. Reduced multimodal integration of memory features following continuous theta burst stimulation of angular gyrus.

    Science.gov (United States)

    Yazar, Yasemin; Bergström, Zara M; Simons, Jon S

    Lesions of the angular gyrus (AnG) region of human parietal cortex do not cause amnesia, but appear to be associated with reduction in the ability to consciously experience the reliving of previous events. We used continuous theta burst stimulation to test the hypothesis that the cognitive mechanism implicated in this memory deficit might be the integration of retrieved sensory event features into a coherent multimodal memory representation. Healthy volunteers received stimulation to AnG or a vertex control site after studying stimuli that each comprised a visual object embedded in a scene, with the name of the object presented auditorily. Participants were then asked to make memory judgments about the studied stimuli that involved recollection of single event features (visual or auditory), or required integration of event features within the same modality, or across modalities. Participants' ability to retrieve context features from across multiple modalities was significantly reduced after AnG stimulation compared to stimulation of the vertex. This effect was observed only for the integration of cross-modal context features but not for integration of features within the same modality, and could not be accounted for by task difficulty as performance was matched across integration conditions following vertex stimulation. These results support the hypothesis that AnG is necessary for the multimodal integration of distributed cortical episodic features into a unified conscious representation that enables the experience of remembering. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Seasonality of Water Chemistry, Carbonate Production, and Biometric Features of Two Species of Chara in a Shallow Clear Water Lake

    Directory of Open Access Journals (Sweden)

    Andrzej Pukacz

    2014-01-01

    Full Text Available The objective of this study was to analyze the temporal variability of biometric features and the carbonate production of two charophytes: Chara polyacantha A. Braun and Chara rudis A. Braun against the background of the physical-chemical properties of water. The investigation was carried out in a small, mid-forest Lake Jasne (western Poland. It is a polymictic, mesotrophic, hardwater ecosystem dominated by charophyte vegetation. Each month, 10 individuals of each species were characterized in terms of morphometric features, fresh and dry weight, and the percentage of calcium carbonate. Additionally, physical-chemical parameters of the water were studied. The results of physical-chemical analyses indicated similar habitat conditions for both species. Despite smaller dry weight C. polyacantha was characterized by greater morphological variability and higher rates of growth and percentage share of calcium carbonate in dry mass than C. rudis. The percentage of calcium carbonates in dry mass did not differ significantly between the species and exceeded 60%, reaching the maximum (76% in C. polyacantha in July and August. For both species, distinct correlations between the structure of biomass and morphological features were found. The obtained results show the great importance of charophyte vegetation in carbon cycling and functioning of lake ecosystems.

  20. A concatenated coding scheme for biometric template protection

    NARCIS (Netherlands)

    Shao, X.; Xu, H.; Veldhuis, Raymond N.J.; Slump, Cornelis H.

    2012-01-01

    Cryptography may mitigate the privacy problem in biometric recognition systems. However, cryptography technologies lack error-tolerance and biometric samples cannot be reproduced exactly, rising the robustness problem. The biometric template protection system needs a good feature extraction

  1. Exploiting Higher Order and Multi-modal Features for 3D Object Detection

    DEFF Research Database (Denmark)

    Kiforenko, Lilita

    that describe object visual appearance such as shape, colour, texture etc. This thesis focuses on robust object detection and pose estimation of rigid objects using 3D information. The thesis main contributions are novel feature descriptors together with object detection and pose estimation algorithms....... The initial work introduces a feature descriptor that uses edge categorisation in combination with a local multi-modal histogram descriptor in order to detect objects with little or no texture or surface variation. The comparison is performed with a state-of-the-art method, which is outperformed...... of the methods work well for one type of objects in a specific scenario, in another scenario or with different objects they might fail, therefore more robust solutions are required. The typical problem solution is the design of robust feature descriptors, where feature descriptors contain information...

  2. Appearance-based human gesture recognition using multimodal features for human computer interaction

    Science.gov (United States)

    Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

    2011-03-01

    The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

  3. Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

    Science.gov (United States)

    Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

    2015-12-01

    Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. Feature Fusion Algorithm for Multimodal Emotion Recognition from Speech and Facial Expression Signal

    Directory of Open Access Journals (Sweden)

    Han Zhiyan

    2016-01-01

    Full Text Available In order to overcome the limitation of single mode emotion recognition. This paper describes a novel multimodal emotion recognition algorithm, and takes speech signal and facial expression signal as the research subjects. First, fuse the speech signal feature and facial expression signal feature, get sample sets by putting back sampling, and then get classifiers by BP neural network (BPNN. Second, measure the difference between two classifiers by double error difference selection strategy. Finally, get the final recognition result by the majority voting rule. Experiments show the method improves the accuracy of emotion recognition by giving full play to the advantages of decision level fusion and feature level fusion, and makes the whole fusion process close to human emotion recognition more, with a recognition rate 90.4%.

  5. An investigation of face and fingerprint feature-fusion guidelines

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-05-01

    Full Text Available There are a lack of multi-modal biometric fusion guidelines at the feature-level. This paper investigates face and fingerprint features in the form of their strengths and weaknesses. This serves as a set of guidelines to authors that are planning...

  6. Discovery and fusion of salient multimodal features toward news story segmentation

    Science.gov (United States)

    Hsu, Winston; Chang, Shih-Fu; Huang, Chih-Wei; Kennedy, Lyndon; Lin, Ching-Yung; Iyengar, Giridharan

    2003-12-01

    In this paper, we present our new results in news video story segmentation and classification in the context of TRECVID video retrieval benchmarking event 2003. We applied and extended the Maximum Entropy statistical model to effectively fuse diverse features from multiple levels and modalities, including visual, audio, and text. We have included various features such as motion, face, music/speech types, prosody, and high-level text segmentation information. The statistical fusion model is used to automatically discover relevant features contributing to the detection of story boundaries. One novel aspect of our method is the use of a feature wrapper to address different types of features -- asynchronous, discrete, continuous and delta ones. We also developed several novel features related to prosody. Using the large news video set from the TRECVID 2003 benchmark, we demonstrate satisfactory performance (F1 measures up to 0.76 in ABC news and 0.73 in CNN news), present how these multi-level multi-modal features construct the probabilistic framework, and more importantly observe an interesting opportunity for further improvement.

  7. Evolutionary Algorithms Application Analysis in Biometric Systems

    Directory of Open Access Journals (Sweden)

    N. Goranin

    2010-01-01

    Full Text Available Wide usage of biometric information for person identity verification purposes, terrorist acts prevention measures and authenticationprocess simplification in computer systems has raised significant attention to reliability and efficiency of biometricsystems. Modern biometric systems still face many reliability and efficiency related issues such as reference databasesearch speed, errors while recognizing of biometric information or automating biometric feature extraction. Current scientificinvestigations show that application of evolutionary algorithms may significantly improve biometric systems. In thisarticle we provide a comprehensive review of main scientific research done in sphere of evolutionary algorithm applicationfor biometric system parameter improvement.

  8. Haptic exploration of fingertip-sized geometric features using a multimodal tactile sensor

    Science.gov (United States)

    Ponce Wong, Ruben D.; Hellman, Randall B.; Santos, Veronica J.

    2014-06-01

    Haptic perception remains a grand challenge for artificial hands. Dexterous manipulators could be enhanced by "haptic intelligence" that enables identification of objects and their features via touch alone. Haptic perception of local shape would be useful when vision is obstructed or when proprioceptive feedback is inadequate, as observed in this study. In this work, a robot hand outfitted with a deformable, bladder-type, multimodal tactile sensor was used to replay four human-inspired haptic "exploratory procedures" on fingertip-sized geometric features. The geometric features varied by type (bump, pit), curvature (planar, conical, spherical), and footprint dimension (1.25 - 20 mm). Tactile signals generated by active fingertip motions were used to extract key parameters for use as inputs to supervised learning models. A support vector classifier estimated order of curvature while support vector regression models estimated footprint dimension once curvature had been estimated. A distal-proximal stroke (along the long axis of the finger) enabled estimation of order of curvature with an accuracy of 97%. Best-performing, curvature-specific, support vector regression models yielded R2 values of at least 0.95. While a radial-ulnar stroke (along the short axis of the finger) was most helpful for estimating feature type and size for planar features, a rolling motion was most helpful for conical and spherical features. The ability to haptically perceive local shape could be used to advance robot autonomy and provide haptic feedback to human teleoperators of devices ranging from bomb defusal robots to neuroprostheses.

  9. An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

    KAUST Repository

    Li, Huibin

    2015-07-29

    We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

  10. An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

    KAUST Repository

    Li, Huibin; Ding, Huaxiong; Huang, Di; Wang, Yunhong; Zhao, Xi; Morvan, Jean-Marie; Chen, Liming

    2015-01-01

    We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

  11. 3D biometrics systems and applications

    CERN Document Server

    Zhang, David

    2013-01-01

    Includes discussions on popular 3D imaging technologies, combines them with biometric applications, and then presents real 3D biometric systems Introduces many efficient 3D feature extraction, matching, and fusion algorithms Techniques presented have been supported by experimental results using various 3D biometric classifications

  12. Beyond Biometrics

    NARCIS (Netherlands)

    van den Broek, Egon

    Throughout the last 40 years, the essence of automated identification of users has remained the same. In this article, a new class of biometrics is proposed that is founded on processing biosignals, as opposed to images. After a brief introduction on biometrics, biosignals are discussed, including

  13. Detection of relationships among multi-modal brain imaging meta-features via information flow.

    Science.gov (United States)

    Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

    2018-01-15

    Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is

  14. Sagittal Thoracic and Lumbar Spine Profiles in Upright Standing and Lying Prone Positions Among Healthy Subjects: Influence of Various Biometric Features.

    Science.gov (United States)

    Salem, Walid; Coomans, Ysaline; Brismée, Jean-Michel; Klein, Paul; Sobczak, Stéphane; Dugailly, Pierre-Michel

    2015-08-01

    A prospective study was performed on the assessment of both thoracic and lumbar spine sagittal profiles (from C7 to S1). To propose a new noninvasive method for measuring the spine curvatures in standing and lying prone positions and to analyze their relationship with various biometric characteristics. Modifications of spine curvatures (i.e. lordosis or kyphosis) are of importance in the development of spinal disorders. Studies have emphasized the development of new devices to measure the spine sagittal profiles using a noninvasive and low-cost method. To date, it has not been applied for analyzing both lumbar and thoracic alterations for various positioning. Seventy-five healthy subjects (mean 22.6 ± 4.3 yr) were recruited to participate in this study. Thoracic and lumbar sagittal profiles were assessed in standing and lying prone positions using a 3D digitizer. In addition, several biometric data were collected including maximal trunk isometric strength for flexion and extension movement. Statistical analysis consisted in data comparisons of spine profiles and a multivariate analysis including biometric features, to classify individuals considering low within- and high between-variability. Kyphosis and lordosis angles decreased significantly from standing to lying prone position by an average of 13.4° and 16.6°, respectively. Multivariate analysis showed a sample clustering of 3 homogenous subgroups. The first group displayed larger lordosis and flexibility, and had low data values for height, weight, and strength. The second group had lower values than the overall trend of the whole sample, whereas the third group had larger score values for the torques, height, weight, waist, body mass index, and kyphosis angle but a reduced flexibility. The present results demonstrate a significant effect of the positioning on both thoracic and lumbar spine sagittal profiles and highlight the use of cluster analysis to categorize subgroups after biometric characteristics

  15. FUSING SPEECH SIGNAL AND PALMPRINT FEATURES FOR AN SECURED AUTHENTICATION SYSTEM

    Directory of Open Access Journals (Sweden)

    P.K. Mahesh

    2011-11-01

    Full Text Available In the application of Biometric authentication, personal identification is regarded as an effective method for automatic recognition, with a high confidence, a person’s identity. Using multimodal biometric systems we typically get better performance compare to single biometric modality. This paper proposes the multimodal biometrics system for identity verification using two traits, i.e., speech signal and palmprint. Integrating the palmprint and speech information increases robustness of person authentication. The proposed system is designed for applications where the training data contains a speech signal and palmprint. It is well known that the performance of person authentication using only speech signal or palmprint is deteriorated by feature changes with time. The final decision is made by fusion at matching score level architecture in which feature vectors are created independently for query measures and are then compared to the enrolment templates, which are stored during database preparation.

  16. MULTIMODAL CLASSIFICATION OF DEMENTIA USING FUNCTIONAL DATA, ANATOMICAL FEATURES AND 3D INVARIANT SHAPE DESCRIPTORS.

    Science.gov (United States)

    Mikhno, Arthur; Nuevo, Pablo Martinez; Devanand, Davangere P; Parsey, Ramin V; Laine, Andrew F

    2012-01-01

    Multimodality classification of Alzheimer's disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), is of interest to the medical community. We improve on prior classification frameworks by incorporating multiple features from MRI and PET data obtained with multiple radioligands, fluorodeoxyglucose (FDG) and Pittsburg compound B (PIB). We also introduce a new MRI feature, invariant shape descriptors based on 3D Zernike moments applied to the hippocampus region. Classification performance is evaluated on data from 17 healthy controls (CTR), 22 MCI, and 17 AD subjects. Zernike significantly outperforms volume, accuracy (Zernike to volume): CTR/AD (90.7% to 71.6%), CTR/MCI (76.2% to 60.0%), MCI/AD (84.3% to 65.5%). Zernike also provides comparable and complementary performance to PET. Optimal accuracy is achieved when Zernike and PET features are combined (accuracy, specificity, sensitivity), CTR/AD (98.8%, 99.5%, 98.1%), CTR/MCI (84.3%, 82.9%, 85.9%) and MCI/AD (93.3%, 93.6%, 93.3%).

  17. A multi-biometric feature-fusion framework for improved uni-modal and multi-modal human identification

    CSIR Research Space (South Africa)

    Brown, K

    2016-05-01

    Full Text Available after basic pre-processing, consist- ing of image alignment, pixel normalization and histogram equalization. The following results relate to the various face and fingerprint datasets only. Local Binary Pattern Histogram (LBPH) proved to be a versatile... descriptor by increasing the radius in correlation to the interpolated neighbours. The modified ELBP operator significantly outperformed the histogram equalization and pixel normalization under dynamic lighting conditions. This was used before the LOG filter...

  18. Spinal focal lesion detection in multiple myeloma using multimodal image features

    Science.gov (United States)

    Fränzle, Andrea; Hillengass, Jens; Bendl, Rolf

    2015-03-01

    Multiple myeloma is a tumor disease in the bone marrow that affects the skeleton systemically, i.e. multiple lesions can occur in different sites in the skeleton. To quantify overall tumor mass for determining degree of disease and for analysis of therapy response, volumetry of all lesions is needed. Since the large amount of lesions in one patient impedes manual segmentation of all lesions, quantification of overall tumor volume is not possible until now. Therefore development of automatic lesion detection and segmentation methods is necessary. Since focal tumors in multiple myeloma show different characteristics in different modalities (changes in bone structure in CT images, hypointensity in T1 weighted MR images and hyperintensity in T2 weighted MR images), multimodal image analysis is necessary for the detection of focal tumors. In this paper a pattern recognition approach is presented that identifies focal lesions in lumbar vertebrae based on features from T1 and T2 weighted MR images. Image voxels within bone are classified using random forests based on plain intensities and intensity value derived features (maximum, minimum, mean, median) in a 5 x 5 neighborhood around a voxel from both T1 and T2 weighted MR images. A test data sample of lesions in 8 lumbar vertebrae from 4 multiple myeloma patients can be classified at an accuracy of 95% (using a leave-one-patient-out test). The approach provides a reasonable delineation of the example lesions. This is an important step towards automatic tumor volume quantification in multiple myeloma.

  19. A bimodal biometric identification system

    Science.gov (United States)

    Laghari, Mohammad S.; Khuwaja, Gulzar A.

    2013-03-01

    Biometrics consists of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. Physicals are related to the shape of the body. Behavioral are related to the behavior of a person. However, biometric authentication systems suffer from imprecision and difficulty in person recognition due to a number of reasons and no single biometrics is expected to effectively satisfy the requirements of all verification and/or identification applications. Bimodal biometric systems are expected to be more reliable due to the presence of two pieces of evidence and also be able to meet the severe performance requirements imposed by various applications. This paper presents a neural network based bimodal biometric identification system by using human face and handwritten signature features.

  20. MR image features predicting hemorrhagic transformation in acute cerebral infarction: a multimodal study

    International Nuclear Information System (INIS)

    Liu, Chunming; Xu, Liang; Dong, Longchun; Liu, Zhenxing; Yang, Jun; Liu, Jun; Dong, Zhengchao; Khursheed, Aiman

    2015-01-01

    The aims of this study were to observe magnetic resonance imaging (MRI) features and the frequency of hemorrhagic transformation (HT) in patients with acute cerebral infarction and to identify the risk factors of HT. We first performed multimodal MRI (anatomical, diffusion weighted, and susceptibility weighted) scans on 87 patients with acute cerebral infarction within 24 hours after symptom onset and documented the image findings. We then performed follow-up examinations 3 days to 2 weeks after the onset or whenever the conditions of the patients worsened within 3 days. We utilized univariate statistics to identify the correlations between HT and image features and used multivariate logistical regression to correct for confounding factors to determine relevant independent image features of HT. HT was observed in 17 out of total 87 patients (19.5 %). The infarct size (p = 0.021), cerebral microbleeds (CMBs) (p = 0.004), relative apparent diffusion (rADC) (p = 0.023), and venous anomalies (p = 0.000) were significantly related with HT in the univariate statistics. Multivariate analysis demonstrated that CMBs (odd ratio (OR) = 0.082; 95 % confidence interval (CI) = 0.011-0.597; p = 0.014), rADC (OR = 0.000; 95 % CI = 0.000-0.692; p = 0.041), and venous anomalies (OR = 0.066; 95 % CI = 0.011-0.403; p = 0.003) were independent risk factors for HT. The frequency of HT is 19.5 % in this study. CMBs, rADC, and venous anomalies are independent risk factors for HT of acute cerebral infarction. (orig.)

  1. MR image features predicting hemorrhagic transformation in acute cerebral infarction: a multimodal study

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Chunming; Xu, Liang; Dong, Longchun; Liu, Zhenxing; Yang, Jun; Liu, Jun [Tianjin Union Medicine Centre, Department of Radiology, Tianjin (China); Dong, Zhengchao [Columbia University, Translational Imaging and MRI Unit, Department of Psychiatry, New York, NY (United States); New York State Psychiatric Institute, New York, NY (United States); Khursheed, Aiman [Tianjin Medical University, International Medical School, Tianjin (China)

    2015-11-15

    The aims of this study were to observe magnetic resonance imaging (MRI) features and the frequency of hemorrhagic transformation (HT) in patients with acute cerebral infarction and to identify the risk factors of HT. We first performed multimodal MRI (anatomical, diffusion weighted, and susceptibility weighted) scans on 87 patients with acute cerebral infarction within 24 hours after symptom onset and documented the image findings. We then performed follow-up examinations 3 days to 2 weeks after the onset or whenever the conditions of the patients worsened within 3 days. We utilized univariate statistics to identify the correlations between HT and image features and used multivariate logistical regression to correct for confounding factors to determine relevant independent image features of HT. HT was observed in 17 out of total 87 patients (19.5 %). The infarct size (p = 0.021), cerebral microbleeds (CMBs) (p = 0.004), relative apparent diffusion (rADC) (p = 0.023), and venous anomalies (p = 0.000) were significantly related with HT in the univariate statistics. Multivariate analysis demonstrated that CMBs (odd ratio (OR) = 0.082; 95 % confidence interval (CI) = 0.011-0.597; p = 0.014), rADC (OR = 0.000; 95 % CI = 0.000-0.692; p = 0.041), and venous anomalies (OR = 0.066; 95 % CI = 0.011-0.403; p = 0.003) were independent risk factors for HT. The frequency of HT is 19.5 % in this study. CMBs, rADC, and venous anomalies are independent risk factors for HT of acute cerebral infarction. (orig.)

  2. Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer’s Disease

    Science.gov (United States)

    Jie, Biao; Cheng, Bo

    2014-01-01

    Accurate diagnosis of Alzheimer’s disease (AD), as well as its pro-dromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method. PMID:24505676

  3. Modular biometric system

    Science.gov (United States)

    Hsu, Charles; Viazanko, Michael; O'Looney, Jimmy; Szu, Harold

    2009-04-01

    Modularity Biometric System (MBS) is an approach to support AiTR of the cooperated and/or non-cooperated standoff biometric in an area persistent surveillance. Advanced active and passive EOIR and RF sensor suite is not considered here. Neither will we consider the ROC, PD vs. FAR, versus the standoff POT in this paper. Our goal is to catch the "most wanted (MW)" two dozens, separately furthermore ad hoc woman MW class from man MW class, given their archrivals sparse front face data basis, by means of various new instantaneous input called probing faces. We present an advanced algorithm: mini-Max classifier, a sparse sample realization of Cramer-Rao Fisher bound of the Maximum Likelihood classifier that minimize the dispersions among the same woman classes and maximize the separation among different man-woman classes, based on the simple feature space of MIT Petland eigen-faces. The original aspect consists of a modular structured design approach at the system-level with multi-level architectures, multiple computing paradigms, and adaptable/evolvable techniques to allow for achieving a scalable structure in terms of biometric algorithms, identification quality, sensors, database complexity, database integration, and component heterogenity. MBS consist of a number of biometric technologies including fingerprints, vein maps, voice and face recognitions with innovative DSP algorithm, and their hardware implementations such as using Field Programmable Gate arrays (FPGAs). Biometric technologies and the composed modularity biometric system are significant for governmental agencies, enterprises, banks and all other organizations to protect people or control access to critical resources.

  4. BIOMETRIC AUTHENTICATION SYSTEM USING RPI

    OpenAIRE

    Fatema A. Shaikh*; Prof.S.O.Rajankar

    2016-01-01

    A biometric authentication system acquires biometric sample such as fingerprint. The fingerprint signifies physiological features of an individual.This is a system which maintains the attendance records of students automatically. In this designing of an efficient module that comprises of a fingerprint sensor to manage the attendance records of students. This module enrolls the student’s as well as staff’s fingerprints. This enrolling is a onetime process and their fingerprints will be stored...

  5. A Novel Algorithm for Feature Level Fusion Using SVM Classifier for Multibiometrics-Based Person Identification

    Directory of Open Access Journals (Sweden)

    Ujwalla Gawande

    2013-01-01

    Full Text Available Recent times witnessed many advancements in the field of biometric and ultimodal biometric fields. This is typically observed in the area, of security, privacy, and forensics. Even for the best of unimodal biometric systems, it is often not possible to achieve a higher recognition rate. Multimodal biometric systems overcome various limitations of unimodal biometric systems, such as nonuniversality, lower false acceptance, and higher genuine acceptance rates. More reliable recognition performance is achievable as multiple pieces of evidence of the same identity are available. The work presented in this paper is focused on multimodal biometric system using fingerprint and iris. Distinct textual features of the iris and fingerprint are extracted using the Haar wavelet-based technique. A novel feature level fusion algorithm is developed to combine these unimodal features using the Mahalanobis distance technique. A support-vector-machine-based learning algorithm is used to train the system using the feature extracted. The performance of the proposed algorithms is validated and compared with other algorithms using the CASIA iris database and real fingerprint database. From the simulation results, it is evident that our algorithm has higher recognition rate and very less false rejection rate compared to existing approaches.

  6. Recognition Errors Control in Biometric Identification Cryptosystems

    Directory of Open Access Journals (Sweden)

    Vladimir Ivanovich Vasilyev

    2015-06-01

    Full Text Available The method of biometric cryptosystem designed on the basis of fuzzy extractor, in which main disadvantages of biometric and cryptographic systems are absent, is considered. The main idea of this work is a control of identity recognition errors with use of fuzzy extractor which operates with Reed – Solomon correcting code. The fingerprint features vector is considered as a biometric user identifier.

  7. SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

    OpenAIRE

    S.PON SANGEETHA; DR.M.KARNAN

    2014-01-01

    The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...

  8. User-Centric Key Entropy: Study of Biometric Key Derivation Subject to Spoofing Attacks

    Directory of Open Access Journals (Sweden)

    Lavinia Mihaela Dinca

    2017-02-01

    Full Text Available Biometric data can be used as input for PKI key pair generation. The concept of not saving the private key is very appealing, but the implementation of such a system shouldn’t be rushed because it might prove less secure then current PKI infrastructure. One biometric characteristic can be easily spoofed, so it was believed that multi-modal biometrics would offer more security, because spoofing two or more biometrics would be very hard. This notion, of increased security of multi-modal biometric systems, was disproved for authentication and matching, studies showing that not only multi-modal biometric systems are not more secure, but they introduce additional vulnerabilities. This paper is a study on the implications of spoofing biometric data for retrieving the derived key. We demonstrate that spoofed biometrics can yield the same key, which in turn will lead an attacker to obtain the private key. A practical implementation is proposed using fingerprint and iris as biometrics and the fuzzy extractor for biometric key extraction. Our experiments show what happens when the biometric data is spoofed for both uni-modal systems and multi-modal. In case of multi-modal system tests were performed when spoofing one biometric or both. We provide detailed analysis of every scenario in regard to successful tests and overall key entropy. Our paper defines a biometric PKI scenario and an in depth security analysis for it. The analysis can be viewed as a blueprint for implementations of future similar systems, because it highlights the main security vulnerabilities for bioPKI. The analysis is not constrained to the biometric part of the system, but covers CA security, sensor security, communication interception, RSA encryption vulnerabilities regarding key entropy, and much more.

  9. A Hybrid FPGA/Coarse Parallel Processing Architecture for Multi-modal Visual Feature Descriptors

    DEFF Research Database (Denmark)

    Jensen, Lars Baunegaard With; Kjær-Nielsen, Anders; Alonso, Javier Díaz

    2008-01-01

    This paper describes the hybrid architecture developed for speeding up the processing of so-called multi-modal visual primitives which are sparse image descriptors extracted along contours. In the system, the first stages of visual processing are implemented on FPGAs due to their highly parallel...

  10. Hardware-efficient robust biometric identification from 0.58 second template and 12 features of limb (Lead I) ECG signal using logistic regression classifier.

    Science.gov (United States)

    Sahadat, Md Nazmus; Jacobs, Eddie L; Morshed, Bashir I

    2014-01-01

    The electrocardiogram (ECG), widely known as a cardiac diagnostic signal, has recently been proposed for biometric identification of individuals; however reliability and reproducibility are of research interest. In this paper, we propose a template matching technique with 12 features using logistic regression classifier that achieved high reliability and identification accuracy. Non-invasive ECG signals were captured using our custom-built ambulatory EEG/ECG embedded device (NeuroMonitor). ECG data were collected from healthy subjects (10), between 25-35 years, for 10 seconds per trial. The number of trials from each subject was 10. From each trial, only 0.58 seconds of Lead I ECG data were used as template. Hardware-efficient fiducial point detection technique was implemented for feature extraction. To obtain repeated random sub-sampling validation, data were randomly separated into training and testing sets at a ratio of 80:20. Test data were used to find the classification accuracy. ECG template data with 12 extracted features provided the best performance in terms of accuracy (up to 100%) and processing complexity (computation time of 1.2ms). This work shows that a single limb (Lead I) ECG can robustly identify an individual quickly and reliably with minimal contact and data processing using the proposed algorithm.

  11. Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Muhammad Naveed Iqbal Qureshi

    2017-09-01

    Full Text Available Multimodal features of structural and functional magnetic resonance imaging (MRI of the human brain can assist in the diagnosis of schizophrenia. We performed a classification study on age, sex, and handedness-matched subjects. The dataset we used is publicly available from the Center for Biomedical Research Excellence (COBRE and it consists of two groups: patients with schizophrenia and healthy controls. We performed an independent component analysis and calculated global averaged functional connectivity-based features from the resting-state functional MRI data for all the cortical and subcortical anatomical parcellation. Cortical thickness along with standard deviation, surface area, volume, curvature, white matter volume, and intensity measures from the cortical parcellation, as well as volume and intensity from sub-cortical parcellation and overall volume of cortex features were extracted from the structural MRI data. A novel hybrid weighted feature concatenation method was used to acquire maximal 99.29% (P < 0.0001 accuracy which preserves high discriminatory power through the weight of the individual feature type. The classification was performed by an extreme learning machine, and its efficiency was compared to linear and non-linear (radial basis function support vector machines, linear discriminant analysis, and random forest bagged tree ensemble algorithms. This article reports the predictive accuracy of both unimodal and multimodal features after 10-by-10-fold nested cross-validation. A permutation test followed the classification experiment to assess the statistical significance of the classification results. It was concluded that, from a clinical perspective, this feature concatenation approach may assist the clinicians in schizophrenia diagnosis.

  12. Four Machine Learning Algorithms for Biometrics Fusion: A Comparative Study

    Directory of Open Access Journals (Sweden)

    I. G. Damousis

    2012-01-01

    Full Text Available We examine the efficiency of four machine learning algorithms for the fusion of several biometrics modalities to create a multimodal biometrics security system. The algorithms examined are Gaussian Mixture Models (GMMs, Artificial Neural Networks (ANNs, Fuzzy Expert Systems (FESs, and Support Vector Machines (SVMs. The fusion of biometrics leads to security systems that exhibit higher recognition rates and lower false alarms compared to unimodal biometric security systems. Supervised learning was carried out using a number of patterns from a well-known benchmark biometrics database, and the validation/testing took place with patterns from the same database which were not included in the training dataset. The comparison of the algorithms reveals that the biometrics fusion system is superior to the original unimodal systems and also other fusion schemes found in the literature.

  13. Optimal Face-Iris Multimodal Fusion Scheme

    Directory of Open Access Journals (Sweden)

    Omid Sharifi

    2016-06-01

    Full Text Available Multimodal biometric systems are considered a way to minimize the limitations raised by single traits. This paper proposes new schemes based on score level, feature level and decision level fusion to efficiently fuse face and iris modalities. Log-Gabor transformation is applied as the feature extraction method on face and iris modalities. At each level of fusion, different schemes are proposed to improve the recognition performance and, finally, a combination of schemes at different fusion levels constructs an optimized and robust scheme. In this study, CASIA Iris Distance database is used to examine the robustness of all unimodal and multimodal schemes. In addition, Backtracking Search Algorithm (BSA, a novel population-based iterative evolutionary algorithm, is applied to improve the recognition accuracy of schemes by reducing the number of features and selecting the optimized weights for feature level and score level fusion, respectively. Experimental results on verification rates demonstrate a significant improvement of proposed fusion schemes over unimodal and multimodal fusion methods.

  14. A lightweight approach for biometric template protection

    Science.gov (United States)

    Al-Assam, Hisham; Sellahewa, Harin; Jassim, Sabah

    2009-05-01

    Privacy and security are vital concerns for practical biometric systems. The concept of cancelable or revocable biometrics has been proposed as a solution for biometric template security. Revocable biometric means that biometric templates are no longer fixed over time and could be revoked in the same way as lost or stolen credit cards are. In this paper, we describe a novel and an efficient approach to biometric template protection that meets the revocability property. This scheme can be incorporated into any biometric verification scheme while maintaining, if not improving, the accuracy of the original biometric system. However, we shall demonstrate the result of applying such transforms on face biometric templates and compare the efficiency of our approach with that of the well-known random projection techniques. We shall also present the results of experimental work on recognition accuracy before and after applying the proposed transform on feature vectors that are generated by wavelet transforms. These results are based on experiments conducted on a number of well-known face image databases, e.g. Yale and ORL databases.

  15. Using Biometric Characteristics to Increase ITS Security

    Directory of Open Access Journals (Sweden)

    Miroslav Bača

    2007-11-01

    Full Text Available Terrorist attacks in New York City and Washington, Districtof Columbia on the morning of September 11, 2001 havechanged our lives. The secwity problem became very importantregarding all spheres of human activities. Tracking persons(employees, customers etc. in ITS (Intelligent Transport Systemis a huge problem. Biometrics offers a very good solutionfor this problem and is today maybe one of the most promisingtechniques for person's secure verification and authentication;biometric system also features some advantages when comparedto other security systems. When using a biometric systemone has to be careful because the functionality of a biometricapplication can be dramatically aggravated if inappropriatebiometric features are selected. Classification of biometric featureson contact and contactless, or distinction between"strong" and "soft" biometric features gives a framework for usingbiometric features, but it does not ensure that biometric featŁtres are implemented at a satisfactory level. The usage ofmultimodal or unimodal biometric system can significantly increasethe system security but it also opens plenty of questionslike privacy etc. This paper describes the implementation ofbiometric features which can be used in ITS, and delineates anew model of usage.

  16. Societal and ethical implications of anti-spoofing technologies in biometrics.

    Science.gov (United States)

    Rebera, Andrew P; Bonfanti, Matteo E; Venier, Silvia

    2014-03-01

    Biometric identification is thought to be less vulnerable to fraud and forgery than are traditional forms of identification. However biometric identification is not without vulnerabilities. In a 'spoofing attack' an artificial replica of an individual's biometric trait is used to induce a system to falsely infer that individual's presence. Techniques such as liveness-detection and multi-modality, as well as the development of new and emerging modalities, are intended to secure biometric identification systems against such threats. Unlike biometrics in general, the societal and ethical issues raised by spoofing and anti-spoofing techniques have not received much attention. This paper examines these issues.

  17. Comparing of athletic performance and biometric features of selected teenagers based on the specific talent identification pattern of Karate with elite athletes

    Directory of Open Access Journals (Sweden)

    seyed Ehsan Naghibi

    2017-12-01

    Conclusion: According to that no significant difference in both groups between athletic performance and biometric parameters except one variable, we can conclude that the process of talent identification in the club studied, in order to distinguish and talented people from other potentially effective. Also according to the native data used in the analysis of the tests in this process can be patterns of biometric indices based on talent and sport performance in karate developed.

  18. Multispectral biometrics systems and applications

    CERN Document Server

    Zhang, David; Gong, Yazhuo

    2016-01-01

    Describing several new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris recognition technologies, this book analyzes a number of efficient feature extraction, matching and fusion algorithms and how potential systems have been developed. Focusing on how to develop new biometric technologies based on the requirements of applications, and how to design efficient algorithms to deliver better performance, the work is based on the author’s research with experimental results under different challenging conditions described in the text. The book offers a valuable resource for researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, biometrics, and security applications, amongst others.

  19. Mobile networks for biometric data analysis

    CERN Document Server

    Madrid, Natividad; Seepold, Ralf; Orcioni, Simone

    2016-01-01

    This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and high user acceptance. It comprises the peer-reviewed papers from the international workshop on the subject that was held in Ancona, Italy, in October 2014 and featured sessions on ICT for health care, biometric data in automotive and home applications, embedded systems for biometric data analysis, biometric data analysis: EMG and ECG, and ICT for gait analysis. The background to the book is the challenge posed by the prevention and treatment of common, widespread chronic diseases in modern, aging societies. Capture of biometric data is a cornerstone for any analysis and treatment strategy. The latest advances in sensor technology allow accurate data measurement in a non-intrusive way, and in many cases it is necessary to provide online monitoring and real-time data capturing to support a patient’s prevention pl...

  20. Biometric Template Security

    OpenAIRE

    Abhishek Nagar; Karthik Nandakumar; Anil K. Jain

    2008-01-01

    Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorizat...

  1. Cancelable Biometrics - A Survey

    OpenAIRE

    Indira Chakravarthy; VVSSS. Balaram; B. Eswara Reddy

    2011-01-01

    In recent times Biometrics has emerged as a reliable, convenient and effective method of user authentication. However, with the increasing use of biometrics in several diverse applications, concerns about the privacy and security of biometric data contained in the database systems has increased. It is therefore imperative that Biometric systems instill confidence in the general public, by demonstrating that, these systems are robust, have low error rates and are tamper proof. In this context,...

  2. Privacy-Preserving Biometric Authentication: Challenges and Directions

    Directory of Open Access Journals (Sweden)

    Elena Pagnin

    2017-01-01

    Full Text Available An emerging direction for authenticating people is the adoption of biometric authentication systems. Biometric credentials are becoming increasingly popular as a means of authenticating people due to the wide range of advantages that they provide with respect to classical authentication methods (e.g., password-based authentication. The most characteristic feature of this authentication method is the naturally strong bond between a user and her biometric credentials. This very same advantageous property, however, raises serious security and privacy concerns in case the biometric trait gets compromised. In this article, we present the most challenging issues that need to be taken into consideration when designing secure and privacy-preserving biometric authentication protocols. More precisely, we describe the main threats against privacy-preserving biometric authentication systems and give directions on possible countermeasures in order to design secure and privacy-preserving biometric authentication protocols.

  3. Transfer learning for bimodal biometrics recognition

    Science.gov (United States)

    Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

    2013-10-01

    Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

  4. Moving-Talker, Speaker-Independent Feature Study, and Baseline Results Using the CUAVE Multimodal Speech Corpus

    Directory of Open Access Journals (Sweden)

    Patterson Eric K

    2002-01-01

    Full Text Available Strides in computer technology and the search for deeper, more powerful techniques in signal processing have brought multimodal research to the forefront in recent years. Audio-visual speech processing has become an important part of this research because it holds great potential for overcoming certain problems of traditional audio-only methods. Difficulties, due to background noise and multiple speakers in an application environment, are significantly reduced by the additional information provided by visual features. This paper presents information on a new audio-visual database, a feature study on moving speakers, and on baseline results for the whole speaker group. Although a few databases have been collected in this area, none has emerged as a standard for comparison. Also, efforts to date have often been limited, focusing on cropped video or stationary speakers. This paper seeks to introduce a challenging audio-visual database that is flexible and fairly comprehensive, yet easily available to researchers on one DVD. The Clemson University Audio-Visual Experiments (CUAVE database is a speaker-independent corpus of both connected and continuous digit strings totaling over 7000 utterances. It contains a wide variety of speakers and is designed to meet several goals discussed in this paper. One of these goals is to allow testing of adverse conditions such as moving talkers and speaker pairs. A feature study of connected digit strings is also discussed. It compares stationary and moving talkers in a speaker-independent grouping. An image-processing-based contour technique, an image transform method, and a deformable template scheme are used in this comparison to obtain visual features. This paper also presents methods and results in an attempt to make these techniques more robust to speaker movement. Finally, initial baseline speaker-independent results are included using all speakers, and conclusions as well as suggested areas of research are

  5. Disguised face identification using multi-modal features in a quaternionic form

    DEFF Research Database (Denmark)

    Apostolopoulos, George; Tzitzilonis, Vasileios; Kappatos, Vassilios

    2017-01-01

    Disguised face recognition is considered as very challenging and important problem in the face recognition field. A disguised face recognition algorithm is proposed using quaternionic representation. The feature extraction module is accomplished with a new method, decomposing each face image...... that the proposed algorithm can achieve high recognition results under disguised conditions....

  6. Investigating and comparing multimodal biometric techniques

    OpenAIRE

    2009-01-01

    M.Sc. Determining the identity of a person has become vital in today’s world. Emphasis on security has become increasingly more common in the last few decades, not only in Information Technology, but across all industries. One of the main principles of security is that a system only be accessed by a legitimate user. According to the ISO 7498/2 document [1] (an international standard which defines an information security system architecture) there are 5 pillars of information security. Thes...

  7. SecurePhone: a mobile phone with biometric authentication and e-signature support for dealing secure transactions on the fly

    Science.gov (United States)

    Ricci, R.; Chollet, G.; Crispino, M. V.; Jassim, S.; Koreman, J.; Olivar-Dimas, M.; Garcia-Salicetti, S.; Soria-Rodriguez, P.

    2006-05-01

    This article presents an overview of the SecurePhone project, with an account of the first results obtained. SecurePhone's primary aim is to realise a mobile phone prototype - the 'SecurePhone' - in which biometrical authentication enables users to deal secure, dependable transactions over a mobile network. The SecurePhone is based on a commercial PDA-phone, supplemented with specific software modules and a customised SIM card. It integrates in a single environment a number of advanced features: access to cryptographic keys through strong multimodal biometric authentication; appending and verification of digital signatures; real-time exchange and interactive modification of (esigned) documents and voice recordings. SecurePhone's 'biometric recogniser' is based on original research. A fused combination of three different biometric methods - speaker, face and handwritten signature verification - is exploited, with no need for dedicated hardware components. The adoption of non-intrusive, psychologically neutral biometric techniques is expected to mitigate rejection problems that often inhibit the social use of biometrics, and speed up the spread of e-signature technology. Successful biometric authentication grants access to SecurePhone's built-in esignature services through a user-friendly interface. Special emphasis is accorded to the definition of a trustworthy security chain model covering all aspects of system operation. The SecurePhone is expected to boost m-commerce and open new scenarios for m-business and m-work, by changing the way people interact and by improving trust and confidence in information technologies, often considered intimidating and difficult to use. Exploitation plans will also explore other application domains (physical and logical access control, securised mobile communications).

  8. Ontology-aided feature correlation for multi-modal urban sensing

    Science.gov (United States)

    Misra, Archan; Lantra, Zaman; Jayarajah, Kasthuri

    2016-05-01

    The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

  9. Biometric Template Security

    Directory of Open Access Journals (Sweden)

    Abhishek Nagar

    2008-03-01

    Full Text Available Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society.

  10. Biometric recognition via fixation density maps

    Science.gov (United States)

    Rigas, Ioannis; Komogortsev, Oleg V.

    2014-05-01

    This work introduces and evaluates a novel eye movement-driven biometric approach that employs eye fixation density maps for person identification. The proposed feature offers a dynamic representation of the biometric identity, storing rich information regarding the behavioral and physical eye movement characteristics of the individuals. The innate ability of fixation density maps to capture the spatial layout of the eye movements in conjunction with their probabilistic nature makes them a particularly suitable option as an eye movement biometrical trait in cases when free-viewing stimuli is presented. In order to demonstrate the effectiveness of the proposed approach, the method is evaluated on three different datasets containing a wide gamut of stimuli types, such as static images, video and text segments. The obtained results indicate a minimum EER (Equal Error Rate) of 18.3 %, revealing the perspectives on the utilization of fixation density maps as an enhancing biometrical cue during identification scenarios in dynamic visual environments.

  11. Biometric citizenship and alienage

    DEFF Research Database (Denmark)

    Stenum, Helle

    . This paper asks if and how biometric techniques are the basis of a re-structuring of management of migration and mobility: Is the suggestion of biometric identifiers reflecting the withdrawal from the principle of rights applied to human beings as an abstract of the universal individual all being equal......, to the (re)introduction the concept of rights being engraved in your body, depended first and foremost on one’s birth, kinship and geography ? The paper will discuss biometric technology in a historical context and explore the apparent biometric divide between citizens and migrants, the latter positioned......Biometric identifiers (finger prints, face scans, iris scans etc.) have increasingly become a key element in technology of EU border and migration management. SIS II, EURODAC and VIS are centralized systems that contain fingerprints of different groups of non-EU citizen, and the biometric...

  12. A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System

    Science.gov (United States)

    Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

    2012-01-01

    Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing. PMID:22919273

  13. A survey and proposed framework on the soft biometrics technique for human identification in intelligent video surveillance system.

    Science.gov (United States)

    Kim, Min-Gu; Moon, Hae-Min; Chung, Yongwha; Pan, Sung Bum

    2012-01-01

    Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.

  14. A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System

    Directory of Open Access Journals (Sweden)

    Min-Gu Kim

    2012-01-01

    Full Text Available Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.

  15. Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer.

    Science.gov (United States)

    Cho, In; Kwon, In Gyu; Guner, Ali; Son, Taeil; Kim, Hyoung-Il; Kang, Dae Ryong; Noh, Sung Hoon; Lim, Joon Seok; Hyung, Woo Jin

    2017-10-03

    Preoperative staging of gastric cancer with computed tomography alone exhibits poor diagnostic accuracy, which may lead to improper treatment decisions. We developed novel patient stratification criteria to select appropriate treatments for gastric cancer patients based on preoperative staging and clinicopathologic features. A total of 5352 consecutive patients who underwent gastrectomy for gastric cancer were evaluated. Preoperative stages were determined according to depth of invasion and nodal involvement on computed tomography. Logistic regression analysis was used to identify clinicopathological factors associated with the likelihood of proper patient stratification. The diagnostic accuracies of computed tomography scans for depth of invasion and nodal involvement were 67.1% and 74.1%, respectively. Among clinicopathologic factors, differentiated tumor histology, tumors smaller than 5 cm, and gross appearance of early gastric cancer on endoscopy were shown to be related to a more advanced stage of disease on preoperative computed tomography imaging than actual pathological stage. Additional consideration of undifferentiated histology, tumors larger than 5 cm, and grossly advanced gastric cancer on endoscopy increased the probability of selecting appropriate treatment from 75.5% to 94.4%. The addition of histology, tumor size, and endoscopic findings to preoperative staging improves patient stratification for more appropriate treatment of gastric cancer.

  16. Touchless fingerprint biometrics

    CERN Document Server

    Labati, Ruggero Donida; Scotti, Fabio

    2015-01-01

    Offering the first comprehensive analysis of touchless fingerprint-recognition technologies, Touchless Fingerprint Biometrics gives an overview of the state of the art and describes relevant industrial applications. It also presents new techniques to efficiently and effectively implement advanced solutions based on touchless fingerprinting.The most accurate current biometric technologies in touch-based fingerprint-recognition systems require a relatively high level of user cooperation to acquire samples of the concerned biometric trait. With the potential for reduced constraints, reduced hardw

  17. Biometric template revocation

    Science.gov (United States)

    Arndt, Craig M.

    2004-08-01

    Biometric are a powerful technology for identifying humans both locally and at a distance. In order to perform identification or verification biometric systems capture an image of some biometric of a user or subject. The image is then converted mathematical to representation of the person call a template. Since we know that every human in the world is different each human will have different biometric images (different fingerprints, or faces, etc.). This is what makes biometrics useful for identification. However unlike a credit card number or a password to can be given to a person and later revoked if it is compromised and biometric is with the person for life. The problem then is to develop biometric templates witch can be easily revoked and reissued which are also unique to the user and can be easily used for identification and verification. In this paper we develop and present a method to generate a set of templates which are fully unique to the individual and also revocable. By using bases set compression algorithms in an n-dimensional orthogonal space we can represent a give biometric image in an infinite number of equally valued and unique ways. The verification and biometric matching system would be presented with a given template and revocation code. The code will then representing where in the sequence of n-dimensional vectors to start the recognition.

  18. Hand-Based Biometric Analysis

    Science.gov (United States)

    Bebis, George (Inventor); Amayeh, Gholamreza (Inventor)

    2015-01-01

    Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.

  19. Biometric identification using local iterated function

    Science.gov (United States)

    Al-Saidi, N. M. G.; Said, M. R. M.

    2014-06-01

    Biometric identification protocol has been received an increasing interest recently. It is a process that determines person identity by making use of their biometric features. A new biometric identification method is presented in this paper based on partial self-similarity that used to identify features within fingerprint images. This approach is already used in Fractal Image Compression (FIC) due to their ability to represent the images by a limited number of affine transformations, and its variation of scale, translation or rotation. These features give the recognition process high impact and good performance. To process data in a fingerprint image, it first converted into digital format using Optical Fingerprint Reader (OFR). The verification process is done by comparing these data with the server data. The system analysis shows that the proposed method is efficient in terms of memory and time complexity.

  20. Practical considerations in privacy preserving biometric face recognition algorithms

    NARCIS (Netherlands)

    Papatsimpa, Ch.; de Groot, J.; Linnartz, J.-P.

    2013-01-01

    The popularity of authentication via fingerprints, iris, face or other biometric features is growing. Hence there is an increasing need to allow a wide variety of verifying parties to have access to biometric template (or reference) data. In this paper, we discuss solutions to ensure that in a

  1. Biometrics and privacy

    NARCIS (Netherlands)

    Grijpink, J.H.A.M.

    2001-01-01

    Biometrics offers many alternatives for protecting our privacy and preventing us from falling victim to crime. Biometrics can even serve as a solid basis for safe anonymous and semi-anonymous legal transactions. In this article Jan Grijpink clarifies which concepts and practical applications this

  2. On Soft Biometrics

    DEFF Research Database (Denmark)

    Nixon, Mark; Correia, Paulo; Nasrollahi, Kamal

    2015-01-01

    Innovation has formed much of the rich history in biometrics. The field of soft biometrics was originally aimed to augment the recognition process by fusion of metrics that were sufficient to discriminate populations rather than individuals. This was later refined to use measures that could be us...

  3. Iris and periocular biometrics

    CERN Document Server

    Rathgeb, Christian

    2017-01-01

    This book provides an overview of scientific fundamentals and principles of iris and periocular biometric recognition. It covers: an introduction to iris and periocular recognition; a selective overview of issues and challenges; soft biometric classification; security aspects; privacy protection and forensics; and future trends.

  4. Securing Iris Templates using Combined User and Soft Biometric based Password Hardened Fuzzy Vault

    OpenAIRE

    Meenakshi, V. S.; Padmavathi, G.

    2010-01-01

    Personal identification and authentication is very crucial in the current scenario. Biometrics plays an important role in this area. Biometric based authentication has proved superior compared to traditional password based authentication. Anyhow biometrics is permanent feature of a person and cannot be reissued when compromised as passwords. To over come this problem, instead of storing the original biometric templates transformed templates can be stored. Whenever the transformation function ...

  5. Multimodal Personal Verification Using Likelihood Ratio for the Match Score Fusion

    Directory of Open Access Journals (Sweden)

    Long Binh Tran

    2017-01-01

    Full Text Available In this paper, the authors present a novel personal verification system based on the likelihood ratio test for fusion of match scores from multiple biometric matchers (face, fingerprint, hand shape, and palm print. In the proposed system, multimodal features are extracted by Zernike Moment (ZM. After matching, the match scores from multiple biometric matchers are fused based on the likelihood ratio test. A finite Gaussian mixture model (GMM is used for estimating the genuine and impostor densities of match scores for personal verification. Our approach is also compared to some different famous approaches such as the support vector machine and the sum rule with min-max. The experimental results have confirmed that the proposed system can achieve excellent identification performance for its higher level in accuracy than different famous approaches and thus can be utilized for more application related to person verification.

  6. Biometric templates selection and update using quality measures

    Science.gov (United States)

    Abboud, Ali J.; Jassim, Sabah A.

    2012-06-01

    To deal with severe variation in recording conditions, most biometric systems acquire multiple biometric samples, at the enrolment stage, for the same person and then extract their individual biometric feature vectors and store them in the gallery in the form of biometric template(s), labelled with the person's identity. The number of samples/templates and the choice of the most appropriate templates influence the performance of the system. The desired biometric template(s) selection technique must aim to control the run time and storage requirements while improving the recognition accuracy of the biometric system. This paper is devoted to elaborating on and discussing a new two stages approach for biometric templates selection and update. This approach uses a quality-based clustering, followed by a special criterion for the selection of an ultimate set of biometric templates from the various clusters. This approach is developed to select adaptively a specific number of templates for each individual. The number of biometric templates depends mainly on the performance of each individual (i.e. gallery size should be optimised to meet the needs of each target individual). These experiments have been conducted on two face image databases and their results will demonstrate the effectiveness of proposed quality-guided approach.

  7. 3D face analysis for demographic biometrics

    Energy Technology Data Exchange (ETDEWEB)

    Tokola, Ryan A [ORNL; Mikkilineni, Aravind K [ORNL; Boehnen, Chris Bensing [ORNL

    2015-01-01

    Despite being increasingly easy to acquire, 3D data is rarely used for face-based biometrics applications beyond identification. Recent work in image-based demographic biometrics has enjoyed much success, but these approaches suffer from the well-known limitations of 2D representations, particularly variations in illumination, texture, and pose, as well as a fundamental inability to describe 3D shape. This paper shows that simple 3D shape features in a face-based coordinate system are capable of representing many biometric attributes without problem-specific models or specialized domain knowledge. The same feature vector achieves impressive results for problems as diverse as age estimation, gender classification, and race classification.

  8. Design and implementation of a contactless multiple hand feature acquisition system

    Science.gov (United States)

    Zhao, Qiushi; Bu, Wei; Wu, Xiangqian; Zhang, David

    2012-06-01

    In this work, an integrated contactless multiple hand feature acquisition system is designed. The system can capture palmprint, palm vein, and palm dorsal vein images simultaneously. Moreover, the images are captured in a contactless manner, that is, users need not to touch any part of the device when capturing. Palmprint is imaged under visible illumination while palm vein and palm dorsal vein are imaged under near infrared (NIR) illumination. The capturing is controlled by computer and the whole process is less than 1 second, which is sufficient for online biometric systems. Based on this device, this paper also implements a contactless hand-based multimodal biometric system. Palmprint, palm vein, palm dorsal vein, finger vein, and hand geometry features are extracted from the captured images. After similarity measure, the matching scores are fused using weighted sum fusion rule. Experimental results show that although the verification accuracy of each uni-modality is not as high as that of state-of-the-art, the fusion result is superior to most of the existing hand-based biometric systems. This result indicates that the proposed device is competent in the application of contactless multimodal hand-based biometrics.

  9. Biometric systems - possibilities and dangers

    OpenAIRE

    Petržilka, Jakub

    2013-01-01

    This bachelor thesis is focused on biometric methods, particularly on fingerprint recognition. First part of thesis places biometric into other methods of people's identification. Identification by token and by knowledge. It also describes the beginning and evolution of biometric. The theoretical part also closely clarify working with data and different view on the biometric systems. The following part of the thesis defines the basic principles of using biometric systems, counting FAR and FRR...

  10. Finger-vein and fingerprint recognition based on a feature-level fusion method

    Science.gov (United States)

    Yang, Jinfeng; Hong, Bofeng

    2013-07-01

    Multimodal biometrics based on the finger identification is a hot topic in recent years. In this paper, a novel fingerprint-vein based biometric method is proposed to improve the reliability and accuracy of the finger recognition system. First, the second order steerable filters are used here to enhance and extract the minutiae features of the fingerprint (FP) and finger-vein (FV). Second, the texture features of fingerprint and finger-vein are extracted by a bank of Gabor filter. Third, a new triangle-region fusion method is proposed to integrate all the fingerprint and finger-vein features in feature-level. Thus, the fusion features contain both the finger texture-information and the minutiae triangular geometry structure. Finally, experimental results performed on the self-constructed finger-vein and fingerprint databases are shown that the proposed method is reliable and precise in personal identification.

  11. Modular Biometric Monitoring System

    Science.gov (United States)

    Chmiel, Alan J. (Inventor); Humphreys, Bradley T. (Inventor)

    2017-01-01

    A modular system for acquiring biometric data includes a plurality of data acquisition modules configured to sample biometric data from at least one respective input channel at a data acquisition rate. A representation of the sampled biometric data is stored in memory of each of the plurality of data acquisition modules. A central control system is in communication with each of the plurality of data acquisition modules through a bus. The central control system is configured to control communication of data, via the bus, with each of the plurality of data acquisition modules.

  12. Security and privacy in biometrics

    CERN Document Server

    Campisi, Patrizio

    2013-01-01

    This important text/reference presents the latest secure and privacy-compliant techniques in automatic human recognition. Featuring viewpoints from an international selection of experts in the field, the comprehensive coverage spans both theory and practical implementations, taking into consideration all ethical and legal issues. Topics and features: presents a unique focus on novel approaches and new architectures for unimodal and multimodal template protection; examines signal processing techniques in the encrypted domain, security and privacy leakage assessment, and aspects of standardizati

  13. DTIC Review: Biometric Security

    National Research Council Canada - National Science Library

    2007-01-01

    ...: Biometrics, the study of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits, is a critical tool used in law enforcement, computer security and homeland defense...

  14. Biometrics Technology Review 2002

    National Research Council Canada - National Science Library

    Blackburn, T

    2003-01-01

    .... The report characterizes the main categories of biometric techniques, with a focus on face recognition, which is the least intrusive but most effective means of applying filters at access points to the country...

  15. Contactless and pose invariant biometric identification using hand surface.

    Science.gov (United States)

    Kanhangad, Vivek; Kumar, Ajay; Zhang, David

    2011-05-01

    This paper presents a novel approach for hand matching that achieves significantly improved performance even in the presence of large hand pose variations. The proposed method utilizes a 3-D digitizer to simultaneously acquire intensity and range images of the user's hand presented to the system in an arbitrary pose. The approach involves determination of the orientation of the hand in 3-D space followed by pose normalization of the acquired 3-D and 2-D hand images. Multimodal (2-D as well as 3-D) palmprint and hand geometry features, which are simultaneously extracted from the user's pose normalized textured 3-D hand, are used for matching. Individual matching scores are then combined using a new dynamic fusion strategy. Our experimental results on the database of 114 subjects with significant pose variations yielded encouraging results. Consistent (across various hand features considered) performance improvement achieved with the pose correction demonstrates the usefulness of the proposed approach for hand based biometric systems with unconstrained and contact-free imaging. The experimental results also suggest that the dynamic fusion approach employed in this work helps to achieve performance improvement of 60% (in terms of EER) over the case when matching scores are combined using the weighted sum rule.

  16. Evaluation of Biometric Systems

    OpenAIRE

    El-Abed , Mohamad; Charrier , Christophe

    2012-01-01

    International audience; Biometrics is considered as a promising solution among traditional methods based on "what we own" (such as a key) or "what we know" (such as a password). It is based on "what we are" and "how we behave". Few people know that biometrics have been used for ages for identification or signature purposes. In 1928 for example, fingerprints were used for women clerical employees of Los Angeles police department as depicted in Figure 1. Fingerprints were also already used as a...

  17. Likelihood-ratio-based biometric verification

    NARCIS (Netherlands)

    Bazen, A.M.; Veldhuis, Raymond N.J.

    2002-01-01

    This paper presents results on optimal similarity measures for biometric verification based on fixed-length feature vectors. First, we show that the verification of a single user is equivalent to the detection problem, which implies that for single-user verification the likelihood ratio is optimal.

  18. Likelihood Ratio-Based Biometric Verification

    NARCIS (Netherlands)

    Bazen, A.M.; Veldhuis, Raymond N.J.

    The paper presents results on optimal similarity measures for biometric verification based on fixed-length feature vectors. First, we show that the verification of a single user is equivalent to the detection problem, which implies that, for single-user verification, the likelihood ratio is optimal.

  19. Practical biometrics from aspiration to implementation

    CERN Document Server

    Ashbourn, Julian

    2015-01-01

    This practically-focused text presents a hands-on guide to making biometric technology work in real-life scenarios. Extensively revised and updated, this new edition takes a fresh look at what it takes to integrate biometrics into wider applications. An emphasis is placed on the importance of a complete understanding of the broader scenario, covering technical, human and implementation factors. This understanding may then be exercised through interactive chapters dealing with educational software utilities and the BANTAM Program Manager. Topics and features: provides a concise introduction t

  20. Securing information using optically generated biometric keys

    Science.gov (United States)

    Verma, Gaurav; Sinha, Aloka

    2016-11-01

    In this paper, we present a new technique to obtain biometric keys by using the fingerprint of a person for an optical image encryption system. The key generation scheme uses the fingerprint biometric information in terms of the amplitude mask (AM) and the phase mask (PM) of the reconstructed fingerprint image that is implemented using the digital holographic technique. Statistical tests have been conducted to check the randomness of the fingerprint PM key that enables its usage as an image encryption key. To explore the utility of the generated biometric keys, an optical image encryption system has been further demonstrated based on the phase retrieval algorithm and the double random phase encoding scheme in which keys for the encryption are used as the AM and the PM key. The advantage associated with the proposed scheme is that the biometric keys’ retrieval requires the simultaneous presence of the fingerprint hologram and the correct knowledge of the reconstruction parameters at the decryption stage, which not only verifies the authenticity of the person but also protects the valuable fingerprint biometric features of the keys. Numerical results are carried out to prove the feasibility and the effectiveness of the proposed encryption system.

  1. A survey of keystroke dynamics biometrics.

    Science.gov (United States)

    Teh, Pin Shen; Teoh, Andrew Beng Jin; Yue, Shigang

    2013-01-01

    Research on keystroke dynamics biometrics has been increasing, especially in the last decade. The main motivation behind this effort is due to the fact that keystroke dynamics biometrics is economical and can be easily integrated into the existing computer security systems with minimal alteration and user intervention. Numerous studies have been conducted in terms of data acquisition devices, feature representations, classification methods, experimental protocols, and evaluations. However, an up-to-date extensive survey and evaluation is not yet available. The objective of this paper is to provide an insightful survey and comparison on keystroke dynamics biometrics research performed throughout the last three decades, as well as offering suggestions and possible future research directions.

  2. Biometric Technologies and Verification Systems

    CERN Document Server

    Vacca, John R

    2007-01-01

    Biometric Technologies and Verification Systems is organized into nine parts composed of 30 chapters, including an extensive glossary of biometric terms and acronyms. It discusses the current state-of-the-art in biometric verification/authentication, identification and system design principles. It also provides a step-by-step discussion of how biometrics works; how biometric data in human beings can be collected and analyzed in a number of ways; how biometrics are currently being used as a method of personal identification in which people are recognized by their own unique corporal or behavior

  3. Can visual evoked potentials be used in biometric identification?

    Science.gov (United States)

    Power, Alan J; Lalor, Edmund C; Reilly, Richard B

    2006-01-01

    Due to known differences in the anatomical structure of the visual pathways and generators in different individuals, the use of visual evoked potentials offers the possibility of an alternative to existing biometrics methods. A study based on visual evoked potentials from 13 individuals was carried out to assess the best combination of temporal, spectral and AR modeling features to realize a robust biometric. From the results it can be concluded that visual evoked potentials show considerable biometric qualities, with classification accuracies reaching a high of 86.54% and that a specific temporal and spectral combination was found to be optimal. Based on these results the visual evoked potential may be a useful tool in biometric identification when used in conjunction with more established biometric methods.

  4. Sensor-fusion-based biometric identity verification

    International Nuclear Information System (INIS)

    Carlson, J.J.; Bouchard, A.M.; Osbourn, G.C.; Martinez, R.F.; Bartholomew, J.W.; Jordan, J.B.; Flachs, G.M.; Bao, Z.; Zhu, L.

    1998-02-01

    Future generation automated human biometric identification and verification will require multiple features/sensors together with internal and external information sources to achieve high performance, accuracy, and reliability in uncontrolled environments. The primary objective of the proposed research is to develop a theoretical and practical basis for identifying and verifying people using standoff biometric features that can be obtained with minimal inconvenience during the verification process. The basic problem involves selecting sensors and discovering features that provide sufficient information to reliably verify a person's identity under the uncertainties caused by measurement errors and tactics of uncooperative subjects. A system was developed for discovering hand, face, ear, and voice features and fusing them to verify the identity of people. The system obtains its robustness and reliability by fusing many coarse and easily measured features into a near minimal probability of error decision algorithm

  5. Impact of environmental factors on biometric matching during human decomposition

    Energy Technology Data Exchange (ETDEWEB)

    Bolme, David S [ORNL; Tokola, Ryan A [ORNL; Boehnen, Chris Bensing [ORNL; Saul, Tiffany B [ORNL; Sauerwein, Kelly A [ORNL; Steadman, Dawnie W [ORNL

    2016-01-01

    Automatic recognition systems are a valuable tool for identifying unknown deceased individuals. Immediately af- ter death fingerprint and face biometric samples are easy to collect using standard sensors and cameras and can be easily matched to anti-mortem biometric samples. Even though post-mortem fingerprints and faces have been used for decades, there are no studies that track these biomet- rics through the later stages of decomposition to determine the length of time the biometrics remain viable. This paper discusses a multimodal dataset of fingerprints, faces, and irises from 14 human cadavers that decomposed outdoors under natural conditions. Results include predictive models relating time and temperature, measured as Accumulated Degree Days (ADD), and season (winter, spring, summer) to the predicted probably of automatic verification using a commercial algorithm.

  6. Biometrics: libraries have begun to see the value of biometrics

    OpenAIRE

    Panneerselvam, Selvi, M. G.

    2007-01-01

    It explains the Biometric Technologies which are becoming the foundation of an extensive array of highly secure identification and personal verification solution. Biometric devices with special reference to finger print recognition is dealt in detail. The benefits of Biometrics in Libraries, its employees and members are highlighted.

  7. Embedded System for Biometric Identification

    OpenAIRE

    Rosli, Ahmad Nasir Che

    2010-01-01

    This chapter describes the design and implementation of an Embedded System for Biometric Identification from hardware and software perspectives. The first part of the chapter describes the idea of biometric identification. This includes the definition of

  8. A Study on EMG-based Biometrics

    OpenAIRE

    Jin Su Kim; Sung Bum Pan

    2017-01-01

    Biometrics is a technology that recognizes user's information by using unique physical features of his or her body such as face, fingerprint, and iris. It also uses behavioral features such as signature, electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG). Among them, the EMG signal is a sign generated when the muscles move, which can be used in various fields such as motion recognition, personal identification, and disease diagnosis. In this paper, we analyze EMG-ba...

  9. Anatomy of Biometric Passports

    Directory of Open Access Journals (Sweden)

    Dominik Malčík

    2012-01-01

    Full Text Available Travelling is becoming available for more and more people. Millions of people are on a way every day. That is why a better control over global human transfer and a more reliable identity check is desired. A recent trend in a field of personal identification documents is to use RFID (Radio Frequency Identification technology and biometrics, especially (but not only in passports. This paper provides an insight into the electronic passports (also called e-passport or ePassport implementation chosen in the Czech Republic. Such a summary is needed for further studies of biometric passports implementation security and biometric passports analysis. A separate description of the Czech solution is a prerequisite for a planned analysis, because of the uniqueness of each implementation. (Each country can choose the implementation details within a range specified by the ICAO (International Civil Aviation Organisation; moreover, specific security mechanisms are optional and can be omitted.

  10. Anatomy of Biometric Passports

    Science.gov (United States)

    Malčík, Dominik; Drahanský, Martin

    2012-01-01

    Travelling is becoming available for more and more people. Millions of people are on a way every day. That is why a better control over global human transfer and a more reliable identity check is desired. A recent trend in a field of personal identification documents is to use RFID (Radio Frequency Identification) technology and biometrics, especially (but not only) in passports. This paper provides an insight into the electronic passports (also called e-passport or ePassport) implementation chosen in the Czech Republic. Such a summary is needed for further studies of biometric passports implementation security and biometric passports analysis. A separate description of the Czech solution is a prerequisite for a planned analysis, because of the uniqueness of each implementation. (Each country can choose the implementation details within a range specified by the ICAO (International Civil Aviation Organisation); moreover, specific security mechanisms are optional and can be omitted). PMID:22969272

  11. Anatomy of biometric passports.

    Science.gov (United States)

    Malčík, Dominik; Drahanský, Martin

    2012-01-01

    Travelling is becoming available for more and more people. Millions of people are on a way every day. That is why a better control over global human transfer and a more reliable identity check is desired. A recent trend in a field of personal identification documents is to use RFID (Radio Frequency Identification) technology and biometrics, especially (but not only) in passports. This paper provides an insight into the electronic passports (also called e-passport or ePassport) implementation chosen in the Czech Republic. Such a summary is needed for further studies of biometric passports implementation security and biometric passports analysis. A separate description of the Czech solution is a prerequisite for a planned analysis, because of the uniqueness of each implementation. (Each country can choose the implementation details within a range specified by the ICAO (International Civil Aviation Organisation); moreover, specific security mechanisms are optional and can be omitted).

  12. A Multimodal Technique for an Embedded Fingerprint Recognizer in Mobile Payment Systems

    Directory of Open Access Journals (Sweden)

    V. Conti

    2009-01-01

    Full Text Available The development and the diffusion of distributed systems, directly connected to recent communication technologies, move people towards the era of mobile and ubiquitous systems. Distributed systems make merchant-customer relationships closer and more flexible, using reliable e-commerce technologies. These systems and environments need many distributed access points, for the creation and management of secure identities and for the secure recognition of users. Traditionally, these access points can be made possible by a software system with a main central server. This work proposes the study and implementation of a multimodal technique, based on biometric information, for identity management and personal ubiquitous authentication. The multimodal technique uses both fingerprint micro features (minutiae and fingerprint macro features (singularity points for robust user authentication. To strengthen the security level of electronic payment systems, an embedded hardware prototype has been also created: acting as self-contained sensors, it performs the entire authentication process on the same device, so that all critical information (e.g. biometric data, account transactions and cryptographic keys, are managed and stored inside the sensor, without any data transmission. The sensor has been prototyped using the Celoxica RC203E board, achieving fast execution time, low working frequency, and good recognition performance.

  13. Body, biometrics and identity.

    Science.gov (United States)

    Mordini, Emilio; Massari, Sonia

    2008-11-01

    According to a popular aphorism, biometrics are turning the human body into a passport or a password. As usual, aphorisms say more than they intend. Taking the dictum seriously, we would be two: ourself and our body. Who are we, if we are not our body? And what is our body without us? The endless history of identification systems teaches that identification is not a trivial fact but always involves a web of economic interests, political relations, symbolic networks, narratives and meanings. Certainly there are reasons for the ethical and political concerns surrounding biometrics but these reasons are probably quite different from those usually alleged.

  14. Binary gabor statistical features for palmprint template protection

    NARCIS (Netherlands)

    Mu, Meiru; Ruan, Qiuqi; Shao, X.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2012-01-01

    The biometric template protection system requires a highquality biometric channel and a well-designed error correction code (ECC). Due to the intra-class variations of biometric data, an efficient fixed-length binary feature extractor is required to provide a high-quality biometric channel so that

  15. eBiometrics: an enhanced multi-biometrics authentication technique for real-time remote applications on mobile devices

    Science.gov (United States)

    Kuseler, Torben; Lami, Ihsan; Jassim, Sabah; Sellahewa, Harin

    2010-04-01

    The use of mobile communication devices with advance sensors is growing rapidly. These sensors are enabling functions such as Image capture, Location applications, and Biometric authentication such as Fingerprint verification and Face & Handwritten signature recognition. Such ubiquitous devices are essential tools in today's global economic activities enabling anywhere-anytime financial and business transactions. Cryptographic functions and biometric-based authentication can enhance the security and confidentiality of mobile transactions. Using Biometric template security techniques in real-time biometric-based authentication are key factors for successful identity verification solutions, but are venerable to determined attacks by both fraudulent software and hardware. The EU-funded SecurePhone project has designed and implemented a multimodal biometric user authentication system on a prototype mobile communication device. However, various implementations of this project have resulted in long verification times or reduced accuracy and/or security. This paper proposes to use built-in-self-test techniques to ensure no tampering has taken place on the verification process prior to performing the actual biometric authentication. These techniques utilises the user personal identification number as a seed to generate a unique signature. This signature is then used to test the integrity of the verification process. Also, this study proposes the use of a combination of biometric modalities to provide application specific authentication in a secure environment, thus achieving optimum security level with effective processing time. I.e. to ensure that the necessary authentication steps and algorithms running on the mobile device application processor can not be undermined or modified by an imposter to get unauthorized access to the secure system.

  16. Secure method for biometric-based recognition with integrated cryptographic functions.

    Science.gov (United States)

    Chiou, Shin-Yan

    2013-01-01

    Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied.

  17. Secure Method for Biometric-Based Recognition with Integrated Cryptographic Functions

    Directory of Open Access Journals (Sweden)

    Shin-Yan Chiou

    2013-01-01

    Full Text Available Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied.

  18. Biometrics Foundation Documents

    Science.gov (United States)

    2009-01-01

    adjudication ( legal ) process. Forensics usually requires days of processing (versus seconds for biometrics) and are held to much higher accuracy...Living Body,” Medicina Philosophica, 11:620-629, 1992. 2 K. Shimizu and K. Yamomoto,“Imaging of Physiological Functions By Laser Transillumination

  19. Biometric Borders and Counterterrorism

    Science.gov (United States)

    2010-12-01

    licenses, credit cards, online retailers , and even military installations all rely on various methods to identify and authenticate individuals in... Malaysia ..................................................................................92 2. 2004—Pakistan and Belgium...first state to establish a national biometric screening program was Malaysia in 1998 with several others that followed suit in 2004–2006, many of which

  20. Unconstrained and contactless hand geometry biometrics.

    Science.gov (United States)

    de-Santos-Sierra, Alberto; Sánchez-Ávila, Carmen; Del Pozo, Gonzalo Bailador; Guerra-Casanova, Javier

    2011-01-01

    This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely support vector machines (SVM) and k-nearest neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.

  1. Unconstrained and Contactless Hand Geometry Biometrics

    Directory of Open Access Journals (Sweden)

    Carmen Sánchez-Ávila

    2011-10-01

    Full Text Available This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM and k-Nearest Neighbour (k-NN. Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.

  2. Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing

    OpenAIRE

    Jin, Zhe; Lai, Yen-Lung; Hwang, Jung-Yeon; Kim, Soohyung; Teoh, Andrew Beng Jin

    2017-01-01

    In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection. With externally generated random parameters, IoM hashing transforms a real-valued biometric feature vector into discrete index (max ranked) hashed code. We demonstrate two realizations from IoM hashing notion, namely Gaussian Random Projection based and Uniformly Random Permutation based hashing schemes. The disc...

  3. Biometric identification based on novel frequency domain facial asymmetry measures

    Science.gov (United States)

    Mitra, Sinjini; Savvides, Marios; Vijaya Kumar, B. V. K.

    2005-03-01

    In the modern world, the ever-growing need to ensure a system's security has spurred the growth of the newly emerging technology of biometric identification. The present paper introduces a novel set of facial biometrics based on quantified facial asymmetry measures in the frequency domain. In particular, we show that these biometrics work well for face images showing expression variations and have the potential to do so in presence of illumination variations as well. A comparison of the recognition rates with those obtained from spatial domain asymmetry measures based on raw intensity values suggests that the frequency domain representation is more robust to intra-personal distortions and is a novel approach for performing biometric identification. In addition, some feature analysis based on statistical methods comparing the asymmetry measures across different individuals and across different expressions is presented.

  4. Multimodal surveillance sensors, algorithms, and systems

    CERN Document Server

    Zhu, Zhigang

    2007-01-01

    From front-end sensors to systems and environmental issues, this practical resource guides you through the many facets of multimodal surveillance. The book examines thermal, vibration, video, and audio sensors in a broad context of civilian and military applications. This cutting-edge volume provides an in-depth treatment of data fusion algorithms that takes you to the core of multimodal surveillance, biometrics, and sentient computing. The book discusses such people and activity topics as tracking people and vehicles and identifying individuals by their speech.Systems designers benefit from d

  5. Optical coherence tomography used for internal biometrics

    Science.gov (United States)

    Chang, Shoude; Sherif, Sherif; Mao, Youxin; Flueraru, Costel

    2007-06-01

    Traditional biometric technologies used for security and person identification essentially deal with fingerprints, hand geometry and face images. However, because all these technologies use external features of human body, they can be easily fooled and tampered with by distorting, modifying or counterfeiting these features. Nowadays, internal biometrics which detects the internal ID features of an object is becoming increasingly important. Being capable of exploring under-skin structure, optical coherence tomography (OCT) system can be used as a powerful tool for internal biometrics. We have applied fiber-optic and full-field OCT systems to detect the multiple-layer 2D images and 3D profile of the fingerprints, which eventually result in a higher discrimination than the traditional 2D recognition methods. More importantly, the OCT based fingerprint recognition has the ability to easily distinguish artificial fingerprint dummies by analyzing the extracted layered surfaces. Experiments show that our OCT systems successfully detected the dummy, which was made of plasticene and was used to bypass the commercially available fingerprint scanning system with a false accept rate (FAR) of 100%.

  6. On Biometrics With Eye Movements.

    Science.gov (United States)

    Zhang, Youming; Juhola, Martti

    2017-09-01

    Eye movements are a relatively novel data source for biometric identification. When video cameras applied to eye tracking become smaller and more efficient, this data source could offer interesting opportunities for the development of eye movement biometrics. In this paper, we study primarily biometric identification as seen as a classification task of multiple classes, and secondarily biometric verification considered as binary classification. Our research is based on the saccadic eye movement signal measurements from 109 young subjects. In order to test the data measured, we use a procedure of biometric identification according to the one-versus-one (subject) principle. In a development from our previous research, which also involved biometric verification based on saccadic eye movements, we now apply another eye movement tracker device with a higher sampling frequency of 250 Hz. The results obtained are good, with correct identification rates at 80-90% at their best.

  7. Bartus Iris biometrics

    Energy Technology Data Exchange (ETDEWEB)

    Johnston, R.; Grace, W.

    1996-07-01

    This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). We won a 1994 R&D 100 Award for inventing the Bartas Iris Verification System. The system has been delivered to a sponsor and is no longer available to us. This technology can verify the identity of a person for purposes of access control, national security, law enforcement, forensics, counter-terrorism, and medical, financial, or scholastic records. The technique is non-invasive, psychologically acceptable, works in real-time, and obtains more biometric data than any other biometric except DNA analysis. This project sought to develop a new, second-generation prototype instrument.

  8. Environmental Testing Methodology in Biometrics

    OpenAIRE

    Fernández Saavedra, Belén; Sánchez Reíllo, Raúl; Alonso Moreno, Raúl; Miguel Hurtado, Óscar

    2010-01-01

    8 pages document + 5-slide presentation.-- Contributed to: 1st International Biometric Performance Conference (IBPC 2010, NIST, Gaithersburg, MD, US, Mar 1-5, 2010). Recently, biometrics is used in many security systems and these systems can be located in different environments. As many experts claim and previous works have demonstrated, environmental conditions influence biometric performance. Nevertheless, there is not a specific methodology for testing this influence at the moment...

  9. Biometrics Go Mainstream

    Science.gov (United States)

    Gale, Doug

    2006-01-01

    Authentication is based on something one knows (e.g., a password), something one has (e.g., a driver's license), or something one is (e.g., a fingerprint). The last of these refers to the use of biometrics for authentication. With the blink of an eye, the touch of a finger, or the uttering of a pass-phrase, colleges and schools can now get deadly…

  10. Analysis and comparison of biometric methods

    OpenAIRE

    Zatloukal, Filip

    2011-01-01

    The thesis deals with biometrics and biometric systems and the possibility to use these systems in the enterprise. Aim of this study is an analysis and description of selected types of biometric identification methods and their advantages and shortcomings. The work is divided into two parts. The first part is theoretical, describes the basic concepts of biometrics, biometric identification criteria, currently used identification systems, the ways of biometric systems use, performance measurem...

  11. Applying intelligent statistical methods on biometric systems

    OpenAIRE

    Betschart, Willie

    2005-01-01

    This master’s thesis work was performed at Optimum Biometric Labs, OBL, located in Karlskrona, Sweden. Optimum Biometric Labs perform independent scenario evaluations to companies who develop biometric devices. The company has a product Optimum preConTM which is surveillance and diagnosis tool for biometric systems. This thesis work’s objective was to develop a conceptual model and implement it as an additional layer above the biometric layer with intelligence about the biometric users. The l...

  12. Practical security and privacy attacks against biometric hashing using sparse recovery

    Science.gov (United States)

    Topcu, Berkay; Karabat, Cagatay; Azadmanesh, Matin; Erdogan, Hakan

    2016-12-01

    Biometric hashing is a cancelable biometric verification method that has received research interest recently. This method can be considered as a two-factor authentication method which combines a personal password (or secret key) with a biometric to obtain a secure binary template which is used for authentication. We present novel practical security and privacy attacks against biometric hashing when the attacker is assumed to know the user's password in order to quantify the additional protection due to biometrics when the password is compromised. We present four methods that can reconstruct a biometric feature and/or the image from a hash and one method which can find the closest biometric data (i.e., face image) from a database. Two of the reconstruction methods are based on 1-bit compressed sensing signal reconstruction for which the data acquisition scenario is very similar to biometric hashing. Previous literature introduced simple attack methods, but we show that we can achieve higher level of security threats using compressed sensing recovery techniques. In addition, we present privacy attacks which reconstruct a biometric image which resembles the original image. We quantify the performance of the attacks using detection error tradeoff curves and equal error rates under advanced attack scenarios. We show that conventional biometric hashing methods suffer from high security and privacy leaks under practical attacks, and we believe more advanced hash generation methods are necessary to avoid these attacks.

  13. Age factors in biometric processing

    CERN Document Server

    Fairhurst, Michael

    2013-01-01

    As biometrics-based identification and identity authentication become increasingly widespread in their deployment, it becomes correspondingly important to consider more carefully issues relating to reliability, usability and inclusion. One factor which is particularly important in this context is that of the relationship between the nature of the measurements extracted from a particular biometric modality and the age of the sample donor, and the effect which age has on physiological and behavioural characteristics invoked in a biometric transaction. In Age Factors in Biometric Processing an in

  14. A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

    Science.gov (United States)

    Sweeney, Elizabeth M.; Vogelstein, Joshua T.; Cuzzocreo, Jennifer L.; Calabresi, Peter A.; Reich, Daniel S.; Crainiceanu, Ciprian M.; Shinohara, Russell T.

    2014-01-01

    Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance. PMID:24781953

  15. Biometrics: Multi-Service Tactics, Techniques, and Procedures for Tactical Employment of Biometrics in Support of Operations

    Science.gov (United States)

    2016-05-01

    Biometrics in Support of Operations Biometrics -at-Sea: Business Rules for South Florida United States...Intelligence Activities Biometrics -Enabled Intelligence USCG Biometrics -at-Sea: Business Rules for...Defense Biometrics United States Intelligence Activities Active Army,

  16. Binary palmprint representation for feature template protection

    NARCIS (Netherlands)

    Mu, Meiru; Ruan, Qiuqi; Shao, X.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2012-01-01

    The major challenge of biometric template protection comes from the intraclass variations of biometric data. The helper data scheme aims to solve this problem by employing the Error Correction Codes (ECC). However, many reported biometric binary features from the same user reach bit error rate (BER)

  17. A biometric method to secure telemedicine systems.

    Science.gov (United States)

    Zhang, G H; Poon, Carmen C Y; Li, Ye; Zhang, Y T

    2009-01-01

    Security and privacy are among the most crucial issues for data transmission in telemedicine systems. This paper proposes a solution for securing wireless data transmission in telemedicine systems, i.e. within a body sensor network (BSN), between the BSN and server as well as between the server and professionals who have assess to the server. A unique feature of this solution is the generation of random keys by physiological data (i.e. a biometric approach) for securing communication at all 3 levels. In the performance analysis, inter-pulse interval of photoplethysmogram is used as an example to generate these biometric keys to protect wireless data transmission. The results of statistical analysis and computational complexity suggest that this type of key is random enough to make telemedicine systems resistant to attacks.

  18. Biometrics — Developments and Potential

    NARCIS (Netherlands)

    Meuwly, Didier; Veldhuis, Raymond N.J.

    2014-01-01

    This article describes the use of biometric technology in forensic science, for the development of new methods and tools, improving the current forensic biometric applications, and allowing for the creation of new ones. The article begins with a definition and a summary of the development of this

  19. Logistic Map for Cancellable Biometrics

    Science.gov (United States)

    Supriya, V. G., Dr; Manjunatha, Ramachandra, Dr

    2017-08-01

    This paper presents design and implementation of secured biometric template protection system by transforming the biometric template using binary chaotic signals and 3 different key streams to obtain another form of template and demonstrating its efficiency by the results and investigating on its security through analysis including, key space analysis, information entropy and key sensitivity analysis.

  20. Biometric Communication Research for Television.

    Science.gov (United States)

    Malik, M. F.

    Biometric communication research is defined as research dealing with the information impact of a film or television show, photographic picture, painting, exhibition, display, or any literary or functional texts or verbal stimuli on human beings, both as individuals and in groups (mass audiences). Biometric communication research consists of a…

  1. Combining Cryptography with EEG Biometrics.

    Science.gov (United States)

    Damaševičius, Robertas; Maskeliūnas, Rytis; Kazanavičius, Egidijus; Woźniak, Marcin

    2018-01-01

    Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

  2. On combining multi-normalization and ancillary measures for the optimal score level fusion of fingerprint and voice biometrics

    Science.gov (United States)

    Mohammed Anzar, Sharafudeen Thaha; Sathidevi, Puthumangalathu Savithri

    2014-12-01

    In this paper, we have considered the utility of multi-normalization and ancillary measures, for the optimal score level fusion of fingerprint and voice biometrics. An efficient matching score preprocessing technique based on multi-normalization is employed for improving the performance of the multimodal system, under various noise conditions. Ancillary measures derived from the feature space and the score space are used in addition to the matching score vectors, for weighing the modalities, based on their relative degradation. Reliability (dispersion) and the separability (inter-/intra-class distance and d-prime statistics) measures under various noise conditions are estimated from the individual modalities, during the training/validation stage. The `best integration weights' are then computed by algebraically combining these measures using the weighted sum rule. The computed integration weights are then optimized against the recognition accuracy using techniques such as grid search, genetic algorithm and particle swarm optimization. The experimental results show that, the proposed biometric solution leads to considerable improvement in the recognition performance even under low signal-to-noise ratio (SNR) conditions and reduces the false acceptance rate (FAR) and false rejection rate (FRR), making the system useful for security as well as forensic applications.

  3. Eye movement identification based on accumulated time feature

    Science.gov (United States)

    Guo, Baobao; Wu, Qiang; Sun, Jiande; Yan, Hua

    2017-06-01

    Eye movement is a new kind of feature for biometrical recognition, it has many advantages compared with other features such as fingerprint, face, and iris. It is not only a sort of static characteristics, but also a combination of brain activity and muscle behavior, which makes it effective to prevent spoofing attack. In addition, eye movements can be incorporated with faces, iris and other features recorded from the face region into multimode systems. In this paper, we do an exploring study on eye movement identification based on the eye movement datasets provided by Komogortsev et al. in 2011 with different classification methods. The time of saccade and fixation are extracted from the eye movement data as the eye movement features. Furthermore, the performance analysis was conducted on different classification methods such as the BP, RBF, ELMAN and SVM in order to provide a reference to the future research in this field.

  4. Improving Speaker Recognition by Biometric Voice Deconstruction

    Directory of Open Access Journals (Sweden)

    Luis Miguel eMazaira-Fernández

    2015-09-01

    Full Text Available Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g. YouTube to broadcast its message. In this new scenario, classical identification methods (such fingerprints or face recognition have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. Through the present paper, a new methodology to characterize speakers will be shown. This methodology is benefiting from the advances achieved during the last years in understanding and modelling voice production. The paper hypothesizes that a gender dependent characterization of speakers combined with the use of a new set of biometric parameters extracted from the components resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract gender-dependent extended biometric parameters are given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions.

  5. Biometric micromixer design

    Energy Technology Data Exchange (ETDEWEB)

    Wang, C.T.; Hu, Z.Y. [National I-Lan Univ., Taiwan (China). Dept. of Mechanical and Electromechanical Engineering; Shaw, C.K. [California Univ., Los Angeles, CA (United States). Dept. of Mechanical and Aerospace Engineering

    2008-07-01

    Fluid mixing in microchannels has many applications, and is particularly important in microfluidic systems for biochemistry and biomedical analysis, or for the production or organic compounds in microreactors. Micromixer development should take into consideration a simple system design with a high mixing efficiency and effective techniques for examining mixing efficiency. Mechanical stirring methods are not suitable for fluid mixing in microchannels because the flow inside microchannels is predominantly laminar and the Reynolds numbers are usually lower than 10. Improving the flexibility and performance of microfluidic systems by incorporating different processes such as fluid handling and fluid motion that cause rapid mixing on micro scale can be challenging. To achieve optimal mixing, an efficient micromixer usually involves complex 3-dimensional geometries which are used to enhance the fluid lamination, stretching and folding. In this study, a biometric concept imitated from distribution of human blood vessel was applied to passive micromixers to promote mixing efficiency. Microchannels of different widths were used to construct the biometric structure. The main advantages of the new design were a high mixing performance and lower pressure drop. Mixing performance was evaluated using a mixing index. The mixing efficiencies in the micromixer under different Reynolds numbers ranging from 1 to 10 were evaluated with a 370 {mu}m device. The main mixing mechanics in this type of passive micromixer was the convection effect. The 2D numerical results revealed that the mixing efficiency of the mixer was 0.876 at Reynolds ratio of 0.85. 9 refs., 3 tabs., 4 figs.

  6. An efficient visualization method for analyzing biometric data

    Science.gov (United States)

    Rahmes, Mark; McGonagle, Mike; Yates, J. Harlan; Henning, Ronda; Hackett, Jay

    2013-05-01

    We introduce a novel application for biometric data analysis. This technology can be used as part of a unique and systematic approach designed to augment existing processing chains. Our system provides image quality control and analysis capabilities. We show how analysis and efficient visualization are used as part of an automated process. The goal of this system is to provide a unified platform for the analysis of biometric images that reduce manual effort and increase the likelihood of a match being brought to an examiner's attention from either a manual or lights-out application. We discuss the functionality of FeatureSCOPE™ which provides an efficient tool for feature analysis and quality control of biometric extracted features. Biometric databases must be checked for accuracy for a large volume of data attributes. Our solution accelerates review of features by a factor of up to 100 times. Review of qualitative results and cost reduction is shown by using efficient parallel visual review for quality control. Our process automatically sorts and filters features for examination, and packs these into a condensed view. An analyst can then rapidly page through screens of features and flag and annotate outliers as necessary.

  7. Biometrics: Accessibility challenge or opportunity?

    Science.gov (United States)

    Blanco-Gonzalo, Ramon; Lunerti, Chiara; Sanchez-Reillo, Raul; Guest, Richard Michael

    2018-01-01

    Biometric recognition is currently implemented in several authentication contexts, most recently in mobile devices where it is expected to complement or even replace traditional authentication modalities such as PIN (Personal Identification Number) or passwords. The assumed convenience characteristics of biometrics are transparency, reliability and ease-of-use, however, the question of whether biometric recognition is as intuitive and straightforward to use is open to debate. Can biometric systems make some tasks easier for people with accessibility concerns? To investigate this question, an accessibility evaluation of a mobile app was conducted where test subjects withdraw money from a fictitious ATM (Automated Teller Machine) scenario. The biometric authentication mechanisms used include face, voice, and fingerprint. Furthermore, we employed traditional modalities of PIN and pattern in order to check if biometric recognition is indeed a real improvement. The trial test subjects within this work were people with real-life accessibility concerns. A group of people without accessibility concerns also participated, providing a baseline performance. Experimental results are presented concerning performance, HCI (Human-Computer Interaction) and accessibility, grouped according to category of accessibility concern. Our results reveal links between individual modalities and user category establishing guidelines for future accessible biometric products.

  8. Biometrics: Accessibility challenge or opportunity?

    Science.gov (United States)

    Lunerti, Chiara; Sanchez-Reillo, Raul; Guest, Richard Michael

    2018-01-01

    Biometric recognition is currently implemented in several authentication contexts, most recently in mobile devices where it is expected to complement or even replace traditional authentication modalities such as PIN (Personal Identification Number) or passwords. The assumed convenience characteristics of biometrics are transparency, reliability and ease-of-use, however, the question of whether biometric recognition is as intuitive and straightforward to use is open to debate. Can biometric systems make some tasks easier for people with accessibility concerns? To investigate this question, an accessibility evaluation of a mobile app was conducted where test subjects withdraw money from a fictitious ATM (Automated Teller Machine) scenario. The biometric authentication mechanisms used include face, voice, and fingerprint. Furthermore, we employed traditional modalities of PIN and pattern in order to check if biometric recognition is indeed a real improvement. The trial test subjects within this work were people with real-life accessibility concerns. A group of people without accessibility concerns also participated, providing a baseline performance. Experimental results are presented concerning performance, HCI (Human-Computer Interaction) and accessibility, grouped according to category of accessibility concern. Our results reveal links between individual modalities and user category establishing guidelines for future accessible biometric products. PMID:29565989

  9. Biometrics: Accessibility challenge or opportunity?

    Directory of Open Access Journals (Sweden)

    Ramon Blanco-Gonzalo

    Full Text Available Biometric recognition is currently implemented in several authentication contexts, most recently in mobile devices where it is expected to complement or even replace traditional authentication modalities such as PIN (Personal Identification Number or passwords. The assumed convenience characteristics of biometrics are transparency, reliability and ease-of-use, however, the question of whether biometric recognition is as intuitive and straightforward to use is open to debate. Can biometric systems make some tasks easier for people with accessibility concerns? To investigate this question, an accessibility evaluation of a mobile app was conducted where test subjects withdraw money from a fictitious ATM (Automated Teller Machine scenario. The biometric authentication mechanisms used include face, voice, and fingerprint. Furthermore, we employed traditional modalities of PIN and pattern in order to check if biometric recognition is indeed a real improvement. The trial test subjects within this work were people with real-life accessibility concerns. A group of people without accessibility concerns also participated, providing a baseline performance. Experimental results are presented concerning performance, HCI (Human-Computer Interaction and accessibility, grouped according to category of accessibility concern. Our results reveal links between individual modalities and user category establishing guidelines for future accessible biometric products.

  10. Comparative and Analysis of Biometric Systems

    OpenAIRE

    Manivannan,; Padma

    2011-01-01

    Biometric as the science of recognizing an individual based on his or her physical or behavioral traits, it is beginning to gain acceptance as a legitimate method for determining an individual identity.Biometric have now been deployed in various commercial, civilian, and national security applications. Biometric described overview of various biometric techniques and the need to be addressed form making biometric technology an effective tool for providing information security.

  11. Biometric Feature Script for Information Security

    Directory of Open Access Journals (Sweden)

    N. E. Gunko

    2010-03-01

    Full Text Available Special studies related to the development of rules for making decisions on the psychological characteristics of the offender in his manuscript handwriting with the goal of ensuring information security.

  12. A Study on EMG-based Biometrics

    Directory of Open Access Journals (Sweden)

    Jin Su Kim

    2017-05-01

    Full Text Available Biometrics is a technology that recognizes user's information by using unique physical features of his or her body such as face, fingerprint, and iris. It also uses behavioral features such as signature, electrocardiogram (ECG, electromyogram (EMG, and electroencephalogram (EEG. Among them, the EMG signal is a sign generated when the muscles move, which can be used in various fields such as motion recognition, personal identification, and disease diagnosis. In this paper, we analyze EMG-based biometrics and implement a motion recognition and personal identification system. The system extracted features using non-uniform filter bank and Waveform Length (WL, and reduces the dimension using Principal Component Analysis (PCA and Linear Discriminant Analysis (LDA. Afterward, it classified the features using Euclidean Distance (ED, Support Vector Machine (SVM and K Nearest Neighbors (KNN. As a result of the motion recognition experiment, 95% of acquired EMG data and 84.66% of UCI data were obtained and as a result of the personal recognition experiment, 85% of acquired EMG data and 88.66% of UCI data were obtained.

  13. Cross Disciplinary Biometric Systems

    CERN Document Server

    Liu, Chengjun

    2012-01-01

    Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance.  Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective ...

  14. Biometrics Research and Engineering Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As the Department of Defense moves forward in its pursuit of integrating biometrics technology into facility access control, the Global War on Terrorism and weapon...

  15. NIST biometric evaluations and developments

    Science.gov (United States)

    Garris, Michael D.; Wilson, Charles L.

    2005-05-01

    This paper presents an R&D framework used by the National Institute of Standards and Technology (NIST) for biometric technology testing and evaluation. The focus of this paper is on fingerprint-based verification and identification. Since 9-11 the NIST Image Group has been mandated by Congress to run a program for biometric technology assessment and biometric systems certification. Four essential areas of activity are discussed: 1) developing test datasets, 2) conducting performance assessment; 3) technology development; and 4) standards participation. A description of activities and accomplishments are provided for each of these areas. In the process, methods of performance testing are described and results from specific biometric technology evaluations are presented. This framework is anticipated to have broad applicability to other technology and application domains.

  16. Biometrics for home networks security

    KAUST Repository

    Ansari, Imran Shafique

    2009-01-01

    Hacking crimes committed to the home networks are increasing. Advanced network protection is not always possible for the home networks. In this paper we will study the ability of using biometric systems for authentication in home networks. ©2009 IEEE.

  17. Transforming Security Screening With Biometrics

    National Research Council Canada - National Science Library

    Hearnsberger, Brian J

    2003-01-01

    ... and identity theft to dramatically improve physical security. Today, biometric technology could be implemented to transform physical security by enhancing screening procedures currently in use at U.S...

  18. Biometrics for home networks security

    KAUST Repository

    Ansari, Imran Shafique; Ahmad, Qutbuddin S.

    2009-01-01

    Hacking crimes committed to the home networks are increasing. Advanced network protection is not always possible for the home networks. In this paper we will study the ability of using biometric systems for authentication in home networks. ©2009

  19. Enhanced biometric access control for mobile devices

    CSIR Research Space (South Africa)

    Brown, Dane

    2017-09-01

    Full Text Available is investigated to determine whether it is comparable to the well-established face biometric. The rest of the paper is organized as follows: Section II presents related face, iris and fused systems found in the literature. Section III discusses the construction.... This diagram is referred to throughout this section, in which the different phases of the system are explained. A. Feature Detection 1) Face: An initial region of interest (ROI) is determined by detecting the face by classifying Histogram of Gaussian (HoG...

  20. Audiovisual Speech Synchrony Measure: Application to Biometrics

    Directory of Open Access Journals (Sweden)

    Gérard Chollet

    2007-01-01

    Full Text Available Speech is a means of communication which is intrinsically bimodal: the audio signal originates from the dynamics of the articulators. This paper reviews recent works in the field of audiovisual speech, and more specifically techniques developed to measure the level of correspondence between audio and visual speech. It overviews the most common audio and visual speech front-end processing, transformations performed on audio, visual, or joint audiovisual feature spaces, and the actual measure of correspondence between audio and visual speech. Finally, the use of synchrony measure for biometric identity verification based on talking faces is experimented on the BANCA database.

  1. Population, growth pattern and biometric characteristics of the ...

    African Journals Online (AJOL)

    The length-frequency distribution, length-weight relationship, condition factor and biometric features of Ethmalosa fimbriata (Bowdich) from Lagos coastal waters, Lagos Lagoon and Lekki Lagoon were investigated for 6 months (January-June). The major fishing methods employed for the collection of the specimens were ...

  2. Possibilities of dynamic biometrics for authentication and the circumstances for using dynamic biometric signature

    Directory of Open Access Journals (Sweden)

    Frantisek Hortai

    2018-01-01

    Full Text Available New information technologies alongside their benefits also bring new dangers with themselves. It is difficult to decide which authentication tool to use and implement in the information systems and electronic documents. The final decision has to compromise among the facts that it faces several conflicting requirements: highly secure tool, to be a user-friendly and user simplicity method, ensure protection against errors and failures of users, speed of authentication and provide these features for a reasonable price. Even when the compromised solution is found it has to fulfill the given technology standards. For the listed reasons the paper argues one of the most natural biometric authentication method the dynamic biometric signature and lists its related standards. The paper also includes measurement evaluation which solves the independence between the person’s signature and device on which it was created

  3. Multimodal Task-Driven Dictionary Learning for Image Classification

    Science.gov (United States)

    2015-12-18

    recognition, multi-view face recognition, multi-view action recognition, and multimodal biometric recognition. It is also shown that, compared to the...improvement in several multi-task learning applications such as target classification, biometric recognitions, and multiview face recognition [12], [14], [17...relevant samples from other modalities for a given unimodal query. However, α1 α2 …αS D1 … Index finger Thumb finger … Iris x1 x2 xS D2 DS … … … J o in

  4. European securitization and biometric identification: the uses of genetic profiling.

    Science.gov (United States)

    Johnson, Paul; Williams, Robin

    2007-01-01

    The recent loss of confidence in textual and verbal methods for validating the identity claims of individual subjects has resulted in growing interest in the use of biometric technologies to establish corporeal uniqueness. Once established, this foundational certainty allows changing biographies and shifting category memberships to be anchored to unchanging bodily surfaces, forms or features. One significant source for this growth has been the "securitization" agendas of nation states that attempt the greater control and monitoring of population movement across geographical borders. Among the wide variety of available biometric schemes, DNA profiling is regarded as a key method for discerning and recording embodied individuality. This paper discusses the current limitations on the use of DNA profiling in civil identification practices and speculates on future uses of the technology with regard to its interoperability with other biometric databasing systems.

  5. Two barriers to realizing the benefits of biometrics: a chain perspective on biometrics and identity fraud as biometrics' real challenge

    Science.gov (United States)

    Grijpink, Jan

    2004-06-01

    Along at least twelve dimensions biometric systems might vary. We need to exploit this variety to manoeuvre biometrics into place to be able to realise its social potential. Subsequently, two perspectives on biometrics are proposed revealing that biometrics will probably be ineffective in combating identity fraud, organised crime and terrorism: (1) the value chain perspective explains the first barrier: our strong preference for large scale biometric systems for general compulsory use. These biometric systems cause successful infringements to spread unnoticed. A biometric system will only function adequately if biometrics is indispensable for solving the dominant chain problem. Multi-chain use of biometrics takes it beyond the boundaries of good manageability. (2) the identity fraud perspective exposes the second barrier: our traditional approach to identity verification. We focus on identity documents, neglecting the person and the situation involved. Moreover, western legal cultures have made identity verification procedures known, transparent, uniform and predictable. Thus, we have developed a blind spot to identity fraud. Biometrics provides good potential to better checking persons, but will probably be used to enhance identity documents. Biometrics will only pay off if it confronts the identity fraudster with less predictable verification processes and more risks of his identity fraud being spotted. Standardised large scale applications of biometrics for general compulsory use without countervailing measures will probably produce the reverse. This contribution tentatively presents a few headlines for an overall biometrics strategy that could better resist identity fraud.

  6. On the Privacy Protection of Biometric Traits: Palmprint, Face, and Signature

    Science.gov (United States)

    Panigrahy, Saroj Kumar; Jena, Debasish; Korra, Sathya Babu; Jena, Sanjay Kumar

    Biometrics are expected to add a new level of security to applications, as a person attempting access must prove who he or she really is by presenting a biometric to the system. The recent developments in the biometrics area have lead to smaller, faster and cheaper systems, which in turn has increased the number of possible application areas for biometric identity verification. The biometric data, being derived from human bodies (and especially when used to identify or verify those bodies) is considered personally identifiable information (PII). The collection, use and disclosure of biometric data — image or template, invokes rights on the part of an individual and obligations on the part of an organization. As biometric uses and databases grow, so do concerns that the personal data collected will not be used in reasonable and accountable ways. Privacy concerns arise when biometric data are used for secondary purposes, invoking function creep, data matching, aggregation, surveillance and profiling. Biometric data transmitted across networks and stored in various databases by others can also be stolen, copied, or otherwise misused in ways that can materially affect the individual involved. As Biometric systems are vulnerable to replay, database and brute-force attacks, such potential attacks must be analysed before they are massively deployed in security systems. Along with security, also the privacy of the users is an important factor as the constructions of lines in palmprints contain personal characteristics, from face images a person can be recognised, and fake signatures can be practised by carefully watching the signature images available in the database. We propose a cryptographic approach to encrypt the images of palmprints, faces, and signatures by an advanced Hill cipher technique for hiding the information in the images. It also provides security to these images from being attacked by above mentioned attacks. So, during the feature extraction, the

  7. Tongue prints: A novel biometric and potential forensic tool.

    Science.gov (United States)

    Radhika, T; Jeddy, Nadeem; Nithya, S

    2016-01-01

    Tongue is a vital internal organ well encased within the oral cavity and protected from the environment. It has unique features which differ from individual to individual and even between identical twins. The color, shape, and surface features are characteristic of every individual, and this serves as a tool for identification. Many modes of biometric systems have come into existence such as fingerprint, iris scan, skin color, signature verification, voice recognition, and face recognition. The search for a new personal identification method secure has led to the use of the lingual impression or the tongue print as a method of biometric authentication. Tongue characteristics exhibit sexual dimorphism thus aiding in the identification of the person. Emerging as a novel biometric tool, tongue prints also hold the promise of a potential forensic tool. This review highlights the uniqueness of tongue prints and its superiority over other biometric identification systems. The various methods of tongue print collection and the classification of tongue features are also elucidated.

  8. Android Based Behavioral Biometric Authentication via Multi-Modal Fusion

    Science.gov (United States)

    2014-06-12

    mobile devices. In order to validate the method proposed in this work data was collected from a Samsung 2 Galaxy S4, running Cyanogenmod version 10.2. The...profile for each user, Al-Khazzar, et al. used a three dimensional maze where users could make diverse decisions and they identified each user from his...performed on a Samsung Galaxy S4 with the following software configuration: • Custom version of Cyanogenmod 10.2 • GApps for Cyanogenmod (Google’s

  9. Synthetic range profiling, ISAR imaging of sea vessels and feature extraction, using a multimode radar to classify targets: initial results from field trials

    CSIR Research Space (South Africa)

    Abdul Gaffar, MY

    2011-04-01

    Full Text Available tanazi@kacst.edu.sa, aazamil@kacst.edu.sa Abstract?This paper describes the design and working principles of an experimental multimode radar with a stepped-frequency Synthetic Range Profiling (SRP) and Inverse Synthetic Aperture Radar (ISAR...

  10. Multimodal Diversity of Postmodernist Fiction Text

    Directory of Open Access Journals (Sweden)

    U. I. Tykha

    2016-12-01

    Full Text Available The article is devoted to the analysis of structural and functional manifestations of multimodal diversity in postmodernist fiction texts. Multimodality is defined as the coexistence of more than one semiotic mode within a certain context. Multimodal texts feature a diversity of semiotic modes in the communication and development of their narrative. Such experimental texts subvert conventional patterns by introducing various semiotic resources – verbal or non-verbal.

  11. Gaze as a biometric

    Science.gov (United States)

    Yoon, Hong-Jun; Carmichael, Tandy R.; Tourassi, Georgia

    2014-03-01

    Two people may analyze a visual scene in two completely different ways. Our study sought to determine whether human gaze may be used to establish the identity of an individual. To accomplish this objective we investigated the gaze pattern of twelve individuals viewing still images with different spatial relationships. Specifically, we created 5 visual "dotpattern" tests to be shown on a standard computer monitor. These tests challenged the viewer's capacity to distinguish proximity, alignment, and perceptual organization. Each test included 50 images of varying difficulty (total of 250 images). Eye-tracking data were collected from each individual while taking the tests. The eye-tracking data were converted into gaze velocities and analyzed with Hidden Markov Models to develop personalized gaze profiles. Using leave-one-out cross-validation, we observed that these personalized profiles could differentiate among the 12 users with classification accuracy ranging between 53% and 76%, depending on the test. This was statistically significantly better than random guessing (i.e., 8.3% or 1 out of 12). Classification accuracy was higher for the tests where the users' average gaze velocity per case was lower. The study findings support the feasibility of using gaze as a biometric or personalized biomarker. These findings could have implications in Radiology training and the development of personalized e-learning environments.

  12. Gaze as a biometric

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Hong-Jun [ORNL; Carmichael, Tandy [Tennessee Technological University; Tourassi, Georgia [ORNL

    2014-01-01

    Two people may analyze a visual scene in two completely different ways. Our study sought to determine whether human gaze may be used to establish the identity of an individual. To accomplish this objective we investigated the gaze pattern of twelve individuals viewing different still images with different spatial relationships. Specifically, we created 5 visual dot-pattern tests to be shown on a standard computer monitor. These tests challenged the viewer s capacity to distinguish proximity, alignment, and perceptual organization. Each test included 50 images of varying difficulty (total of 250 images). Eye-tracking data were collected from each individual while taking the tests. The eye-tracking data were converted into gaze velocities and analyzed with Hidden Markov Models to develop personalized gaze profiles. Using leave-one-out cross-validation, we observed that these personalized profiles could differentiate among the 12 users with classification accuracy ranging between 53% and 76%, depending on the test. This was statistically significantly better than random guessing (i.e., 8.3% or 1 out of 12). Classification accuracy was higher for the tests where the users average gaze velocity per case was lower. The study findings support the feasibility of using gaze as a biometric or personalized biomarker. These findings could have implications in Radiology training and the development of personalized e-learning environments.

  13. Improving Speaker Recognition by Biometric Voice Deconstruction

    Science.gov (United States)

    Mazaira-Fernandez, Luis Miguel; Álvarez-Marquina, Agustín; Gómez-Vilda, Pedro

    2015-01-01

    Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g., YouTube) to broadcast its message. In this new scenario, classical identification methods (such as fingerprints or face recognition) have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. The present study benefits from the advances achieved during last years in understanding and modeling voice production. The paper hypothesizes that a gender-dependent characterization of speakers combined with the use of a set of features derived from the components, resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract the gender-dependent extended biometric parameters is given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions. PMID:26442245

  14. Multimodal fusion of polynomial classifiers for automatic person recgonition

    Science.gov (United States)

    Broun, Charles C.; Zhang, Xiaozheng

    2001-03-01

    With the prevalence of the information age, privacy and personalization are forefront in today's society. As such, biometrics are viewed as essential components of current evolving technological systems. Consumers demand unobtrusive and non-invasive approaches. In our previous work, we have demonstrated a speaker verification system that meets these criteria. However, there are additional constraints for fielded systems. The required recognition transactions are often performed in adverse environments and across diverse populations, necessitating robust solutions. There are two significant problem areas in current generation speaker verification systems. The first is the difficulty in acquiring clean audio signals in all environments without encumbering the user with a head- mounted close-talking microphone. Second, unimodal biometric systems do not work with a significant percentage of the population. To combat these issues, multimodal techniques are being investigated to improve system robustness to environmental conditions, as well as improve overall accuracy across the population. We propose a multi modal approach that builds on our current state-of-the-art speaker verification technology. In order to maintain the transparent nature of the speech interface, we focus on optical sensing technology to provide the additional modality-giving us an audio-visual person recognition system. For the audio domain, we use our existing speaker verification system. For the visual domain, we focus on lip motion. This is chosen, rather than static face or iris recognition, because it provides dynamic information about the individual. In addition, the lip dynamics can aid speech recognition to provide liveness testing. The visual processing method makes use of both color and edge information, combined within Markov random field MRF framework, to localize the lips. Geometric features are extracted and input to a polynomial classifier for the person recognition process. A late

  15. Voice Biometrics for Information Assurance Applications

    National Research Council Canada - National Science Library

    Kang, George

    2002-01-01

    .... The ultimate goal of voice biometrics is to enable the use of voice as a password. Voice biometrics are "man-in-the-loop" systems in which system performance is significantly dependent on human performance...

  16. Biometric National Identification Number Generation for Secure ...

    African Journals Online (AJOL)

    Biometric National Identification Number Generation for Secure Network Authentication Based Fingerprint. ... Username, Password, Remember me, or Register ... In this paper an authentication based finger print biometric system is proposed ...

  17. Biometric Authorization and Registration Systems and Methods

    National Research Council Canada - National Science Library

    Caulfield, H

    2002-01-01

    Biometric authorization and registration systems and methods are disclosed. In one embodiment, the system preferably comprises a firearm that includes a biometric authorization system, a plurality of training computers, and a server...

  18. A framework for biometric playtesting of games

    OpenAIRE

    Janssen, Dirk; Calvi, Licia; Gualeni, Stefano; Foundation of Digital Games Conference

    2013-01-01

    The described framework is meant to assist game developers in using biometric (psychophysiological) methods while playtesting. Biometric methods can give developers a valuable additional window on the playtester's experience.

  19. Digital holographic-based cancellable biometric for personal authentication

    International Nuclear Information System (INIS)

    Verma, Gaurav; Sinha, Aloka

    2016-01-01

    In this paper, we propose a new digital holographic-based cancellable biometric scheme for personal authentication and verification. The realization of cancellable biometric is presented by using an optoelectronic experimental approach, in which an optically recorded hologram of the fingerprint of a person is numerically reconstructed. Each reconstructed feature has its own perspective, which is utilized to generate user-specific fingerprint features by using a feature-extraction process. New representations of the user-specific fingerprint features can be obtained from the same hologram, by changing the reconstruction distance (d) by an amount Δd between the recording plane and the reconstruction plane. This parameter is the key to make the cancellable user-specific fingerprint features using a digital holographic technique, which allows us to choose different reconstruction distances when reissuing the user-specific fingerprint features in the event of compromise. We have shown theoretically that each user-specific fingerprint feature has a unique identity with a high discrimination ability, and the chances of a match between them are minimal. In this aspect, a recognition system has also been demonstrated using the fingerprint biometric of the enrolled person at a particular reconstruction distance. For the performance evaluation of a fingerprint recognition system—the false acceptance ratio, the false rejection ratio and the equal error rate are calculated using correlation. The obtained results show good discrimination ability between the genuine and the impostor populations with the highest recognition rate of 98.23%. (paper)

  20. Biometrics for electronic health records.

    Science.gov (United States)

    Flores Zuniga, Alejandro Enrique; Win, Khin Than; Susilo, Willy

    2010-10-01

    Securing electronic health records, in scenarios in which the provision of care services is share among multiple actors, could become a complex and costly activity. Correct identification of patients and physician, protection of privacy and confidentiality, assignment of access permissions for healthcare providers and resolutions of conflicts rise as main points of concern in the development of interconnected health information networks. Biometric technologies have been proposed as a possible technological solution for these issues due to its ability to provide a mechanism for unique verification of an individual identity. This paper presents an analysis of the benefit as well as disadvantages offered by biometric technology. A comparison between this technology and more traditional identification methods is used to determine the key benefits and flaws of the use biometric in health information systems. The comparison as been made considering the viability of the technologies for medical environments, global security needs, the contemplation of a share care environment and the costs involved in the implementation and maintenance of such technologies. This paper also discusses alternative uses for biometrics technologies in health care environments. The outcome of this analysis lays in the fact that even when biometric technologies offer several advantages over traditional method of identification, they are still in the early stages of providing a suitable solution for a health care environment.

  1. The use of biometrics in IT

    OpenAIRE

    Bílý, Petr

    2009-01-01

    Biometrics is increasingly applied in IT (biometric methods today generally use computer technology), mostly used to authenticate users. The aim of this thesis is to describe and compare two selected biometric methods. These methods are fingerprints and scanning of human face. The contribution of this work is to provide information on biometric identification methods, their advantages and disadvantages, and deployment options. If an organization decides to strengthen their security systems wi...

  2. Securing Biometric Images using Reversible Watermarking

    OpenAIRE

    Thampi, Sabu M.; Jacob, Ann Jisma

    2011-01-01

    Biometric security is a fast growing area. Protecting biometric data is very important since it can be misused by attackers. In order to increase security of biometric data there are different methods in which watermarking is widely accepted. A more acceptable, new important development in this area is reversible watermarking in which the original image can be completely restored and the watermark can be retrieved. But reversible watermarking in biometrics is an understudied area. Reversible ...

  3. Performance Evaluation Of Behavioral Biometric Systems

    OpenAIRE

    Cherifi , Fouad; Hemery , Baptiste; Giot , Romain; Pasquet , Marc; Rosenberger , Christophe

    2009-01-01

    We present in this chapter an overview of techniques for the performance evaluation of behavioral biometric systems. The BioAPI standard that defines the architecture of a biometric system is presented in the first part of the chapter... The general methodology for the evaluation of biometric systems is given including statistical metrics, definition of benchmark databases and subjective evaluation. These considerations rely with the ISO/IEC19795-1 standard describing the biometric performanc...

  4. Can soft biometric traits assist user recognition?

    Science.gov (United States)

    Jain, Anil K.; Dass, Sarat C.; Nandakumar, Karthik

    2004-08-01

    Biometrics is rapidly gaining acceptance as the technology that can meet the ever increasing need for security in critical applications. Biometric systems automatically recognize individuals based on their physiological and behavioral characteristics. Hence, the fundamental requirement of any biometric recognition system is a human trait having several desirable properties like universality, distinctiveness, permanence, collectability, acceptability, and resistance to circumvention. However, a human characteristic that possesses all these properties has not yet been identified. As a result, none of the existing biometric systems provide perfect recognition and there is a scope for improving the performance of these systems. Although characteristics like gender, ethnicity, age, height, weight and eye color are not unique and reliable, they provide some information about the user. We refer to these characteristics as "soft" biometric traits and argue that these traits can complement the identity information provided by the primary biometric identifiers like fingerprint and face. This paper presents the motivation for utilizing soft biometric information and analyzes how the soft biometric traits can be automatically extracted and incorporated in the decision making process of the primary biometric system. Preliminary experiments were conducted on a fingerprint database of 160 users by synthetically generating soft biometric traits like gender, ethnicity, and height based on known statistics. The results show that the use of additional soft biometric user information significantly improves (approximately 6%) the recognition performance of the fingerprint biometric system.

  5. Biometric Score Calibration for Forensic Face Recognition

    NARCIS (Netherlands)

    Ali, Tauseef

    2014-01-01

    When two biometric specimens are compared using an automatic biometric recognition system, a similarity metric called “score‿ can be computed. In forensics, one of the biometric specimens is from an unknown source, for example, from a CCTV footage or a fingermark found at a crime scene and the other

  6. The research and application of multi-biometric acquisition embedded system

    Science.gov (United States)

    Deng, Shichao; Liu, Tiegen; Guo, Jingjing; Li, Xiuyan

    2009-11-01

    The identification technology based on multi-biometric can greatly improve the applicability, reliability and antifalsification. This paper presents a multi-biometric system bases on embedded system, which includes: three capture daughter boards are applied to obtain different biometric: one each for fingerprint, iris and vein of the back of hand; FPGA (Field Programmable Gate Array) is designed as coprocessor, which uses to configure three daughter boards on request and provides data path between DSP (digital signal processor) and daughter boards; DSP is the master processor and its functions include: control the biometric information acquisition, extracts feature as required and responsible for compare the results with the local database or data server through network communication. The advantages of this system were it can acquire three different biometric in real time, extracts complexity feature flexibly in different biometrics' raw data according to different purposes and arithmetic and network interface on the core-board will be the solution of big data scale. Because this embedded system has high stability, reliability, flexibility and fit for different data scale, it can satisfy the demand of multi-biometric recognition.

  7. A novel biometric authentication approach using ECG and EMG signals.

    Science.gov (United States)

    Belgacem, Noureddine; Fournier, Régis; Nait-Ali, Amine; Bereksi-Reguig, Fethi

    2015-05-01

    Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication.

  8. On the Feasibility of Interoperable Schemes in Hand Biometrics

    Directory of Open Access Journals (Sweden)

    Miguel A. Ferrer

    2012-02-01

    Full Text Available Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.

  9. On the feasibility of interoperable schemes in hand biometrics.

    Science.gov (United States)

    Morales, Aythami; González, Ester; Ferrer, Miguel A

    2012-01-01

    Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.

  10. On the Feasibility of Interoperable Schemes in Hand Biometrics

    Science.gov (United States)

    Morales, Aythami; González, Ester; Ferrer, Miguel A.

    2012-01-01

    Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors. PMID:22438714

  11. Tongue prints in biometric authentication: A pilot study.

    Science.gov (United States)

    Jeddy, Nadeem; Radhika, T; Nithya, S

    2017-01-01

    Biometric authentication is an important process for the identification and verification of individuals for security purposes. There are many biometric systems that are currently in use and also being researched. Tongue print is a new biometric authentication tool that is unique and cannot be easily forged because no two tongue prints are similar. The present study aims to evaluate the common morphological features of the tongue and its variations in males and females. The usefulness of alginate impression and dental cast in obtaining the lingual impression was also evaluated. The study sample included twenty participants. The participants were subjected to visual examination following which digital photographs of the dorsal surface of the tongue were taken. Alginate impressions of the tongue were made, and casts were prepared using dental stone. The photographs and the casts were analyzed by two observers separately for the surface morphology including shape, presence or absence of fissures and its pattern of distribution. Three reference points were considered to determine the shape of the tongue. The most common morphological feature on the dorsum of the tongue was the presence of central fissures. Multiple vertical fissures were observed in males whereas single vertical fissure was a common finding in females. The fissures were predominantly shallow in males and deep in females. The tongue was predominantly U shaped in males and females. V-shaped tongue was observed in 25% of females. Tongue prints are useful in biometric authentication. The methodology used in the study is simple, easy and can be adopted by dentists on a regular basis. However, large-scale studies are required to validate the results and also identify other features of the tongue that can be used in forensics and biometric authentication process.

  12. Secure authentication system that generates seed from biometric information.

    Science.gov (United States)

    Kim, Yeojin; Ahn, Jung-Ho; Byun, Hyeran

    2005-02-10

    As biometric recognition techniques are gradually improved, the stability of biometric authentication systems are enhanced. Although bioinformation has properties that make it resistant to fraud, biometric authentication systems are not immune to hacking. We show a secure biometric authentication system (1) to guarantee the integrity of biometric information by mixing data by use of a biometric key and (2) to raise recognition rates by use of bimodal biometrics.

  13. Multimodality and Ambient Intelligence

    NARCIS (Netherlands)

    Nijholt, Antinus; Verhaegh, W.; Aarts, E.; Korst, J.

    2004-01-01

    In this chapter we discuss multimodal interface technology. We present eexamples of multimodal interfaces and show problems and opportunities. Fusion of modalities is discussed and some roadmap discussions on research in multimodality are summarized. This chapter also discusses future developments

  14. Biometric morphing: a novel technique for the analysis of morphologic outcomes after facial surgery.

    Science.gov (United States)

    Pahuta, Markian A; Mainprize, James G; Rohlf, F James; Antonyshyn, Oleh M

    2009-01-01

    The results of facial surgery are intuitively judged in terms of the visible changes in facial features or proportions. However, describing these morphologic outcomes objectively remains a challenge. Biometric morphing addresses this issue by merging statistical shape analysis and image processing. This study describes the implementation of biometric morphing in describing the average morphologic result of facial surgery. The biometric morphing protocol was applied to pre- and postoperative images of the following: (1) 40 dorsal hump reduction rhinoplasties and (2) 20 unilateral enophthalmos repairs. Pre- and postoperative average images (average morphs) were generated. The average morphs provided an objective rendering of nasal and periorbital morphology, which summarized the average features and extent of deformity in a population of patients. Subtle alterations in morphology after surgery, which would otherwise be difficult to identify or demonstrate, were clearly illustrated. Biometric morphing is an effective instrument for describing average facial morphology in a population of patients.

  15. Biometrics Technology : Attitudes & influencing factors when trying to adopt this technology in Blekinge healthcare

    OpenAIRE

    Iqbal, Irfan; Qadir, Bilal

    2012-01-01

    Context. Biometric technology is a secure and convenient identification method and it does not need to remember complex passwords, nor smart cards, keys, and the like. Biometrics is the measurable characteristics of individuals based on their behavioral patterns or physiological features that can be used to verify or recognize their identity. Physical characteristics include fingerprints, palm or hand geometry, iris, retina, and facial characteristics. Behavioral characteristics include signat...

  16. Biometric security based on ECG

    NARCIS (Netherlands)

    Ma, L.; Groot, de J.A.; Linnartz, J.P.M.G.

    2011-01-01

    Recently the electrocardiogram (ECG) has been proposed as a novel biometric. This paper aims to construct a reliable ECG verification system, in terms of privacy protection. To this end, an improved expression to estimate the capacity in the autocorrelation (AC) of the ECG is derived, which not only

  17. NCI: DCTD: Biometric Research Program

    Science.gov (United States)

    The Biometric Research Program (BRP) is the statistical and biomathematical component of the Division of Cancer Treatment, Diagnosis and Centers (DCTDC). Its members provide statistical leadership for the national and international research programs of the division in developmental therapeutics, developmental diagnostics, diagnostic imaging and clinical trials.

  18. Hand Grasping Synergies As Biometrics.

    Science.gov (United States)

    Patel, Vrajeshri; Thukral, Poojita; Burns, Martin K; Florescu, Ionut; Chandramouli, Rajarathnam; Vinjamuri, Ramana

    2017-01-01

    Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements). Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic). Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies) from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies-postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.

  19. NCI: DCTD: Biometric Research Branch

    Science.gov (United States)

    The Biometric Research Branch (BRB) is the statistical and biomathematical component of the Division of Cancer Treatment, Diagnosis and Centers (DCTDC). Its members provide statistical leadership for the national and international research programs of the division in developmental therapeutics, developmental diagnostics, diagnostic imaging and clinical trials.

  20. Hand Grasping Synergies As Biometrics

    Directory of Open Access Journals (Sweden)

    Ramana Vinjamuri

    2017-05-01

    Full Text Available Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements. Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic. Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies—postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.

  1. No age discrimination for biometrics

    CSIR Research Space (South Africa)

    Lessing, MM

    2008-07-01

    Full Text Available . The research considers biometric advancements in the areas of travel and immigration, healthcare, law enforcement and banking. For the purpose of this study, adults are considered the individuals and groups in a working environment. Many of these applications...

  2. Handbook of biometric anti-spoofing trusted biometrics under spoofing attacks

    CERN Document Server

    Marcel, Sébastien; Li, Stan Z

    2014-01-01

    As the plethora of approaches to biometrics and their deployment continues to grow, so too does the need to combat the techniques used to subvert the aim of such biometric systems. Presenting the first definitive study of the subject, this Handbook of Biometric Anti-Spoofing reviews the state of the art in covert attacks against biometric systems, and in deriving countermeasures to these attacks. Across a range of common biometrics, including face, iris, fingerprint, speaker and gait, the book describes spoofing methods and examines the vulnerabilities of biometric systems to these attacks.

  3. Machine Learning-Empowered Biometric Methods for Biomedicine Applications

    Directory of Open Access Journals (Sweden)

    Qingxue Zhang

    2017-07-01

    Full Text Available Nowadays, pervasive computing technologies are paving a promising way for advanced smart health applications. However, a key impediment faced by wide deployment of these assistive smart devices, is the increasing privacy and security issue, such as how to protect access to sensitive patient data in the health record. Focusing on this challenge, biometrics are attracting intense attention in terms of effective user identification to enable confidential health applications. In this paper, we take special interest in two bio-potential-based biometric modalities, electrocardiogram (ECG and electroencephalogram (EEG, considering that they are both unique to individuals, and more reliable than token (identity card and knowledge-based (username/password methods. After extracting effective features in multiple domains from ECG/EEG signals, several advanced machine learning algorithms are introduced to perform the user identification task, including Neural Network, K-nearest Neighbor, Bagging, Random Forest and AdaBoost. Experimental results on two public ECG and EEG datasets show that ECG is a more robust biometric modality compared to EEG, leveraging a higher signal to noise ratio and also more distinguishable morphological patterns. Among different machine learning classifiers, the random forest greatly outperforms the others and owns an identification rate as high as 98%. This study is expected to demonstrate that properly selected biometric empowered by an effective machine learner owns a great potential, to enable confidential biomedicine applications in the era of smart digital health.

  4. Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns

    Directory of Open Access Journals (Sweden)

    Wonki Lee

    2018-03-01

    Full Text Available The electrocardiogram (ECG waveform conveys information regarding the electrical property of the heart. The patterns vary depending on the individual heart characteristics. ECG features can be potentially used for biometric recognition. This study presents a new method using the entire ECG waveform pattern for matching and demonstrates that the approach can potentially be employed for individual biometric identification. Multi-cycle ECG signals were assessed using an ECG measuring circuit, and three electrodes can be patched on the wrists or fingers for considering various measurements. For biometric identification, our-fold cross validation was used in the experiments for assessing how the results of a statistical analysis will generalize to an independent data set. Four different pattern matching algorithms, i.e., cosine similarity, cross correlation, city block distance, and Euclidean distances, were tested to compare the individual identification performances with a single channel of ECG signal (3-wire ECG. To evaluate the pattern matching for biometric identification, the ECG recordings for each subject were partitioned into training and test set. The suggested method obtained a maximum performance of 89.9% accuracy with two heartbeats of ECG signals measured on the wrist and 93.3% accuracy with three heartbeats for 55 subjects. The performance rate with ECG signals measured on the fingers improved up to 99.3% with two heartbeats and 100% with three heartbeats of signals for 20 subjects.

  5. Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns.

    Science.gov (United States)

    Lee, Wonki; Kim, Seulgee; Kim, Daeeun

    2018-03-28

    The electrocardiogram (ECG) waveform conveys information regarding the electrical property of the heart. The patterns vary depending on the individual heart characteristics. ECG features can be potentially used for biometric recognition. This study presents a new method using the entire ECG waveform pattern for matching and demonstrates that the approach can potentially be employed for individual biometric identification. Multi-cycle ECG signals were assessed using an ECG measuring circuit, and three electrodes can be patched on the wrists or fingers for considering various measurements. For biometric identification, our-fold cross validation was used in the experiments for assessing how the results of a statistical analysis will generalize to an independent data set. Four different pattern matching algorithms, i.e., cosine similarity, cross correlation, city block distance, and Euclidean distances, were tested to compare the individual identification performances with a single channel of ECG signal (3-wire ECG). To evaluate the pattern matching for biometric identification, the ECG recordings for each subject were partitioned into training and test set. The suggested method obtained a maximum performance of 89.9% accuracy with two heartbeats of ECG signals measured on the wrist and 93.3% accuracy with three heartbeats for 55 subjects. The performance rate with ECG signals measured on the fingers improved up to 99.3% with two heartbeats and 100% with three heartbeats of signals for 20 subjects.

  6. A biometric authentication model using hand gesture images.

    Science.gov (United States)

    Fong, Simon; Zhuang, Yan; Fister, Iztok; Fister, Iztok

    2013-10-30

    A novel hand biometric authentication method based on measurements of the user's stationary hand gesture of hand sign language is proposed. The measurement of hand gestures could be sequentially acquired by a low-cost video camera. There could possibly be another level of contextual information, associated with these hand signs to be used in biometric authentication. As an analogue, instead of typing a password 'iloveu' in text which is relatively vulnerable over a communication network, a signer can encode a biometric password using a sequence of hand signs, 'i' , 'l' , 'o' , 'v' , 'e' , and 'u'. Subsequently the features from the hand gesture images are extracted which are integrally fuzzy in nature, to be recognized by a classification model for telling if this signer is who he claimed himself to be, by examining over his hand shape and the postures in doing those signs. It is believed that everybody has certain slight but unique behavioral characteristics in sign language, so are the different hand shape compositions. Simple and efficient image processing algorithms are used in hand sign recognition, including intensity profiling, color histogram and dimensionality analysis, coupled with several popular machine learning algorithms. Computer simulation is conducted for investigating the efficacy of this novel biometric authentication model which shows up to 93.75% recognition accuracy.

  7. Biometric Quantization through Detection Rate Optimized Bit Allocation

    Directory of Open Access Journals (Sweden)

    C. Chen

    2009-01-01

    Full Text Available Extracting binary strings from real-valued biometric templates is a fundamental step in many biometric template protection systems, such as fuzzy commitment, fuzzy extractor, secure sketch, and helper data systems. Previous work has been focusing on the design of optimal quantization and coding for each single feature component, yet the binary string—concatenation of all coded feature components—is not optimal. In this paper, we present a detection rate optimized bit allocation (DROBA principle, which assigns more bits to discriminative features and fewer bits to nondiscriminative features. We further propose a dynamic programming (DP approach and a greedy search (GS approach to achieve DROBA. Experiments of DROBA on the FVC2000 fingerprint database and the FRGC face database show good performances. As a universal method, DROBA is applicable to arbitrary biometric modalities, such as fingerprint texture, iris, signature, and face. DROBA will bring significant benefits not only to the template protection systems but also to the systems with fast matching requirements or constrained storage capability.

  8. Heartbeat Signal from Facial Video for Biometric Recognition

    DEFF Research Database (Denmark)

    Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.

    2015-01-01

    Different biometric traits such as face appearance and heartbeat signal from Electrocardiogram (ECG)/Phonocardiogram (PCG) are widely used in the human identity recognition. Recent advances in facial video based measurement of cardio-physiological parameters such as heartbeat rate, respiratory rate......, and blood volume pressure provide the possibility of extracting heartbeat signal from facial video instead of using obtrusive ECG or PCG sensors in the body. This paper proposes the Heartbeat Signal from Facial Video (HSFV) as a new biometric trait for human identity recognition, for the first time...... to the best of our knowledge. Feature extraction from the HSFV is accomplished by employing Radon transform on a waterfall model of the replicated HSFV. The pairwise Minkowski distances are obtained from the Radon image as the features. The authentication is accomplished by a decision tree based supervised...

  9. Machine learning techniques for gait biometric recognition using the ground reaction force

    CERN Document Server

    Mason, James Eric; Woungang, Isaac

    2016-01-01

    This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of ...

  10. Physiological Biometric Authentication Systems Advantages Disadvantages And Future Development A Review

    Directory of Open Access Journals (Sweden)

    Israa M. Alsaadi

    2015-08-01

    Full Text Available Abstract With the fast increasing of the electronic crimes and their related issues deploying a reliable user authentication system became a significant task for both of access control and securing users private data. Human biometric characteristics such as face finger iris scanning voice signature and other features provide a dependable security level for both of the personal and the public use. Many biometric authentication systems have been approached for long time. Due to the uniqueness of human biometrics witch played a master role in degrading imposters attacks. Such authentication models have overcome other traditional security methods like passwords and PIN. This paper aims to briefly address the psychological biometric authentication techniques. Also a brief summary to the advantages disadvantages and future developments of each method is provided in this paper.

  11. Transfer Function Control for Biometric Monitoring System

    Science.gov (United States)

    Chmiel, Alan J. (Inventor); Humphreys, Bradley T. (Inventor); Grodinsky, Carlos M. (Inventor)

    2015-01-01

    A modular apparatus for acquiring biometric data may include circuitry operative to receive an input signal indicative of a biometric condition, the circuitry being configured to process the input signal according to a transfer function thereof and to provide a corresponding processed input signal. A controller is configured to provide at least one control signal to the circuitry to programmatically modify the transfer function of the modular system to facilitate acquisition of the biometric data.

  12. Towards a General Definition of Biometric Systems

    OpenAIRE

    Mirko Cubrilo; Miroslav Baca; Markus Schatten

    2009-01-01

    A foundation for closing the gap between biometrics in the narrower and the broader perspective is presented trough a conceptualization of biometric systems in both perspectives. A clear distinction between verification, identification and classification systems is made as well as shown that there are additional classes of biometric systems. In the end a Unified Modeling Language model is developed showing the connections between the two perspectives.

  13. BIOMETRIC AUTHENTICATION USING NONPARAMETRIC METHODS

    OpenAIRE

    S V Sheela; K R Radhika

    2010-01-01

    The physiological and behavioral trait is employed to develop biometric authentication systems. The proposed work deals with the authentication of iris and signature based on minimum variance criteria. The iris patterns are preprocessed based on area of the connected components. The segmented image used for authentication consists of the region with large variations in the gray level values. The image region is split into quadtree components. The components with minimum variance are determine...

  14. Mobile biometric device (MBD) technology :

    Energy Technology Data Exchange (ETDEWEB)

    Aldridge, Chris D.

    2013-06-01

    Mobile biometric devices (MBDs) capable of both enrolling individuals in databases and performing identification checks of subjects in the field are seen as an important capability for military, law enforcement, and homeland security operations. The technology is advancing rapidly. The Department of Homeland Security Science and Technology Directorate through an Interagency Agreement with Sandia sponsored a series of pilot projects to obtain information for the first responder law enforcement community on further identification of requirements for mobile biometric device technology. Working with 62 different jurisdictions, including components of the Department of Homeland Security, Sandia delivered a series of reports on user operation of state-of-the-art mobile biometric devices. These reports included feedback information on MBD usage in both operational and exercise scenarios. The findings and conclusions of the project address both the limitations and possibilities of MBD technology to improve operations. Evidence of these possibilities can be found in the adoption of this technology by many agencies today and the cooperation of several law enforcement agencies in both participating in the pilot efforts and sharing of information about their own experiences in efforts undertaken separately.

  15. Emerging Biometric Modalities: Challenges and Opportunities

    Science.gov (United States)

    Gafurov, Davrondzhon

    Recent advances in sensor technology and wide spread use of various electronics (computers, PDA, mobile phones etc.) provide new opportunities for capturing and analyses of novel physiological and behavioural traits of human beings for biometric authentication. This paper presents an overview of several such types of human characteristics that have been proposed as alternatives to traditional types of biometrics. We refer to these characteristics as emerging biometrics. We survey various types of emerging modalities and techniques, and discuss their pros and cons. Emerging biometrics faces several limitations and challenges which include subject population coverage (focusing mostly on adults); unavailability of benchmark databases; little research with respect to vulnerability/robustness against attacks; and some privacy concerns they may arise. In addition, recognition performance of emerging modalities are generally less accurate compared to the traditional biometrics. Despite all of these emerging biometrics posses their own benefits and advantages compared to traditional biometrics which makes them still attractive for research. First of all, emerging biometrics can always serve as a complementary source for identity information; they can be suitable in applications where traditional biometrics are difficult or impossible to adapt such as continuous or periodic re-verification of the user's identity etc.

  16. Encryption Technology based on Human Biometrics

    Directory of Open Access Journals (Sweden)

    Wei Yang

    2017-08-01

    Full Text Available The research progress of encryption technologies based on human biometrics is reviewed in this paper.The technologies that utilize human biometrics to make information encryption and identity authentication,and the technologies which combine biometrics encryption with optical encryption methods are introduced in detail.The advantages and disadvantages of these encryption systems are discussed,and the obstacles in practical applications are pointed out.Finally,the prospect of the new encryption technologies that are based on human biometrics are predicted.

  17. Identification and authentication. Common biometric methods review

    OpenAIRE

    Lysak, A.

    2012-01-01

    Major biometric methods used for identification and authentication purposes in modern computing systems are considered in the article. Basic classification, application areas and key differences are given.

  18. Biometric Collection, Transmission and Storage Standards. Version 1.1

    National Research Council Canada - National Science Library

    2006-01-01

    This document provides a comprehensive technical reference that lists published biometric standards and describes their applicability to the biometric functions described in the Capstone Concept of Operations (CONOPS...

  19. Dynamic detection-rate-based bit allocation with genuine interval concealment for binary biometric representation.

    Science.gov (United States)

    Lim, Meng-Hui; Teoh, Andrew Beng Jin; Toh, Kar-Ann

    2013-06-01

    Biometric discretization is a key component in biometric cryptographic key generation. It converts an extracted biometric feature vector into a binary string via typical steps such as segmentation of each feature element into a number of labeled intervals, mapping of each interval-captured feature element onto a binary space, and concatenation of the resulted binary output of all feature elements into a binary string. Currently, the detection rate optimized bit allocation (DROBA) scheme is one of the most effective biometric discretization schemes in terms of its capability to assign binary bits dynamically to user-specific features with respect to their discriminability. However, we learn that DROBA suffers from potential discriminative feature misdetection and underdiscretization in its bit allocation process. This paper highlights such drawbacks and improves upon DROBA based on a novel two-stage algorithm: 1) a dynamic search method to efficiently recapture such misdetected features and to optimize the bit allocation of underdiscretized features and 2) a genuine interval concealment technique to alleviate crucial information leakage resulted from the dynamic search. Improvements in classification accuracy on two popular face data sets vindicate the feasibility of our approach compared with DROBA.

  20. Resting State EEG-based biometrics for individual identification using convolutional neural networks.

    Science.gov (United States)

    Lan Ma; Minett, James W; Blu, Thierry; Wang, William S-Y

    2015-08-01

    Biometrics is a growing field, which permits identification of individuals by means of unique physical features. Electroencephalography (EEG)-based biometrics utilizes the small intra-personal differences and large inter-personal differences between individuals' brainwave patterns. In the past, such methods have used features derived from manually-designed procedures for this purpose. Another possibility is to use convolutional neural networks (CNN) to automatically extract an individual's best and most unique neural features and conduct classification, using EEG data derived from both Resting State with Open Eyes (REO) and Resting State with Closed Eyes (REC). Results indicate that this CNN-based joint-optimized EEG-based Biometric System yields a high degree of accuracy of identification (88%) for 10-class classification. Furthermore, rich inter-personal difference can be found using a very low frequency band (0-2Hz). Additionally, results suggest that the temporal portions over which subjects can be individualized is less than 200 ms.

  1. Spotting and tracking good biometrics with the human visual system

    Science.gov (United States)

    Szu, Harold; Jenkins, Jeffrey; Hsu, Charles

    2011-06-01

    We mathematically model the mammalian Visual System's (VS) capability of spotting objects. How can a hawk see a tiny running rabbit from miles above ground? How could that rabbit see the approaching hawk? This predatorprey interaction draws parallels with spotting a familiar person in a crowd. We assume that mammal eyes use peripheral vision to perceive unexpected changes from our memory, and then use our central vision (fovea) to pay attention. The difference between an image and our memory of that image is usually small, mathematically known as a 'sparse representation'. The VS communicates with the brain using a finite reservoir of neurotransmittents, which produces an on-center and thus off-surround Hubel/Wiesel Mexican hat receptive field. This is the basis of our model. This change detection mechanism could drive our attention, allowing us to hit a curveball. If we are about to hit a baseball, what information extracted by our HVS tells us where to swing? Physical human features such as faces, irises, and fingerprints have been successfully used for identification (Biometrics) for decades, recently including voice and walking style for identification from further away. Biologically, humans must use a change detection strategy to achieve an ordered sparseness and use a sigmoid threshold for noisy measurements in our Hetero-Associative Memory [HAM] classifier for fault tolerant recall. Human biometrics is dynamic, and therefore involves more than just the surface, requiring a 3 dimensional measurement (i.e. Daugman/Gabor iris features). Such a measurement can be achieved using the partial coherence of a laser's reflection from a 3-D biometric surface, creating more degrees of freedom (d.o.f.) to meet the Army's challenge of distant Biometrics. Thus, one might be able to increase the standoff loss of less distinguished degrees of freedom (DOF).

  2. Biometrics can help protect and safeguard.

    Science.gov (United States)

    Oakes, Shaun

    2017-06-01

    Shaun Oakes, managing director at ievo, a north-east England-based manufacturer of biometric fingerprint readers, argues that growing use of biometrics technology can improve security and afford better protection to premises, valuable items, and people, across an ever-busier NHS.

  3. Controlling Leakage of Biometric Information using Dithering

    NARCIS (Netherlands)

    Buhan, I.R.; Doumen, J.M.; Hartel, Pieter H.; Buhan, I.R.; Doumen, J.M.; Hartel, P.H.

    Fuzzy extractors allow cryptographic keys to be generated from noisy, non-uniform biometric data. Fuzzy extractors can be used to authenticate a user to a server without storing her biometric data directly. However, in the Information Theoretic sense fuzzy extractors will leak information about the

  4. Semiparametric Copula Models for Biometric Score Level

    NARCIS (Netherlands)

    Caselli, M.

    2016-01-01

    In biometric recognition systems, biometric samples (images of faces, finger- prints, voices, gaits, etc.) of people are compared and classifiers (matchers) indicate the level of similarity between any pair of samples by a score. If two samples of the same person are compared, a genuine score is

  5. Behavioural Biometrics for Application in Biomedicine

    Czech Academy of Sciences Publication Activity Database

    Schlenker, Anna; Šárek, M.

    2013-01-01

    Roč. 1, č. 1 (2013), s. 56-56 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : biometrics * behavioural biometrics * keystroke dynamics * mouse dynamics Subject RIV: IN - Informatics, Computer Science

  6. Biometric and intelligent decision making support

    CERN Document Server

    Kaklauskas, Arturas

    2015-01-01

    This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area of intelligent decision support systems, biometrics technologies and their integrations. This book is designated for scholars, practitioners and doctoral and master’s degree students in various areas and those who are interested in the latest biometric and intelligent decision making support problems and means for their resolutions, biometric and intelligent decision making support systems and the theory and practice of their integration and the opportunities fo...

  7. Recommendation on the Use of Biometric Technology

    DEFF Research Database (Denmark)

    Juul, Niels Christian

    2013-01-01

    Biometric technology is based on the use of information linked to individuals. Hence, privacy and security in biometric applications becomes a concern and the need to assess such applications thoroughly becomes equally important. Guidelines for application of biometric technology must ensure...... a positive impact on both security and privacy. Based on two cases of biometric application, which have been assessed by the Danish Data Protecting Agency, this chapter present a set of recommendations to legislators, regulators, corporations and individuals on the appropriate use of biometric technologies...... put forward by the Danish Board of Technology. The recommendations are discussed and compared to the similar proposal put forward by the European Article 29 Data Protection Working Party....

  8. Heart Sound Biometric System Based on Marginal Spectrum Analysis

    Science.gov (United States)

    Zhao, Zhidong; Shen, Qinqin; Ren, Fangqin

    2013-01-01

    This work presents a heart sound biometric system based on marginal spectrum analysis, which is a new feature extraction technique for identification purposes. This heart sound identification system is comprised of signal acquisition, pre-processing, feature extraction, training, and identification. Experiments on the selection of the optimal values for the system parameters are conducted. The results indicate that the new spectrum coefficients result in a significant increase in the recognition rate of 94.40% compared with that of the traditional Fourier spectrum (84.32%) based on a database of 280 heart sounds from 40 participants. PMID:23429515

  9. Bridging the gap: from biometrics to forensics.

    Science.gov (United States)

    Jain, Anil K; Ross, Arun

    2015-08-05

    Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment, border crossing, national civil registry and access to restricted facilities. Despite these successful deployments in various fields, there are several existing challenges and new opportunities for person recognition using biometrics. In particular, when biometric data is acquired in an unconstrained environment or if the subject is uncooperative, the quality of the ensuing biometric data may not be amenable for automated person recognition. This is particularly true in crime-scene investigations, where the biological evidence gleaned from a scene may be of poor quality. In this article, we first discuss how biometrics evolved from forensic science and how its focus is shifting back to its origin in order to address some challenging problems. Next, we enumerate the similarities and differences between biometrics and forensics. We then present some applications where the principles of biometrics are being successfully leveraged into forensics in order to solve critical problems in the law enforcement domain. Finally, we discuss new collaborative opportunities for researchers in biometrics and forensics, in order to address hitherto unsolved problems that can benefit society at large. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  10. Privacy-leakage codes for biometric authentication systems

    NARCIS (Netherlands)

    Ignatenko, T.; Willems, F.M.J.

    2014-01-01

    In biometric privacy-preserving authentication systems that are based on key-binding, two terminals observe two correlated biometric sequences. The first terminal selects a secret key, which is independent of the biometric data, binds this secret key to the observed biometric sequence and

  11. User Authentication based on Continuous Touch Biometrics

    Directory of Open Access Journals (Sweden)

    Christina J Kroeze

    2016-12-01

    Full Text Available Mobile devices such as smartphones have until now been protected by traditional authentication methods, including passwords or pattern locks. These authentication mechanisms are difficult to remember and are often disabled, leaving the device vulnerable if stolen. This paper investigates the possibility of unobtrusive, continuous authentication for smartphones based on biometric data collected using a touchscreen. The possibility of authenticating users on a smartphone was evaluated by conducting an experiment simulating real-world touch interaction. Touch data was collected from 30 participants during normal phone use. The touch features were analysed in terms of the information provided for authentication. It was found that features such as finger pressure, location of touch interaction and shape of the finger were important discriminators for authentication. The touch data was also analysed using two classification algorithms to measure the authentication accuracy. The results show that touch data is sufficiently distinct between users to be used in authentication without disrupting normal touch interaction. It is also shown that the raw touch data was more effective in authentication than the aggregated gesture data.

  12. A novel approach to transformed biometrics using successive projections

    Science.gov (United States)

    Gopi, E. S.

    2010-02-01

    Unlike user created password, number of biometrics is limited for creating account in different organizations. Transformed biometrics attempts to solve the problem by transforming the biometric into another form, which is unique to the particular organization. This makes the availability of different transformed biometrics in different organizations transformed from the same biometrics and helps in foolproof transactions. In this article a novel approach to transformed biometrics using successive projection technique is suggested .In the proposed technique, the user can register up to 5*4n-1 organizations if the length of the biometric password is 'n'.

  13. Iris recognition as a biometric method after cataract surgery.

    Science.gov (United States)

    Roizenblatt, Roberto; Schor, Paulo; Dante, Fabio; Roizenblatt, Jaime; Belfort, Rubens

    2004-01-28

    Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery. Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical) distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon. A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described. Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure.

  14. Iris recognition as a biometric method after cataract surgery

    Directory of Open Access Journals (Sweden)

    Roizenblatt Jaime

    2004-01-01

    Full Text Available Abstract Background Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery. Methods Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon. Results A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described. Conclusions Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure.

  15. Novel continuous authentication using biometrics

    Science.gov (United States)

    Dubey, Prakash; Patidar, Rinku; Mishra, Vikas; Norman, Jasmine; Mangayarkarasi, R.

    2017-11-01

    We explore whether a classifier can consistent1y verify c1ients and interact with the computer using camera and behavior of users. In this paper we propose a new way of authentication of user which wi1l capture many images of user in random time and ana1ysis of its touch biometric behavior. In this system experiment the touch conduct of a c1ient/user between an en1istment stage is stored in the database and it is checked its mean time behavior during equa1 partition of time. This touch behavior wi1l ab1e to accept or reject the user. This wi1l modify the use of biometric more accurate to use. In this system the work p1an going to perform is the user wi1l ask single time to a1low to take it picture before 1ogin. Then it wi1l take images of user without permission of user automatica1ly and store in the database. This images and existing image of user wi1l be compare and reject or accept wi1l depend on its comparison. The user touch behavior wi1l keep storing with number of touch make in equa1 amount of time of the user. This touch behavior and image wi1l fina1ly perform authentication of the user automatically.

  16. Biometrics encryption combining palmprint with two-layer error correction codes

    Science.gov (United States)

    Li, Hengjian; Qiu, Jian; Dong, Jiwen; Feng, Guang

    2017-07-01

    To bridge the gap between the fuzziness of biometrics and the exactitude of cryptography, based on combining palmprint with two-layer error correction codes, a novel biometrics encryption method is proposed. Firstly, the randomly generated original keys are encoded by convolutional and cyclic two-layer coding. The first layer uses a convolution code to correct burst errors. The second layer uses cyclic code to correct random errors. Then, the palmprint features are extracted from the palmprint images. Next, they are fused together by XORing operation. The information is stored in a smart card. Finally, the original keys extraction process is the information in the smart card XOR the user's palmprint features and then decoded with convolutional and cyclic two-layer code. The experimental results and security analysis show that it can recover the original keys completely. The proposed method is more secure than a single password factor, and has higher accuracy than a single biometric factor.

  17. Study of Biometric Identification Method Based on Naked Footprint

    Directory of Open Access Journals (Sweden)

    Raji Rafiu King

    2013-10-01

    Full Text Available The scale of deployment of biometric identity-verification systems has recently seen an enormous increase owing to the need for more secure and reliable way of identifying people. Footprint identification which can be defined as the measurement of footprint features for recognizing the identity of a user has surfaced recently. This study is based on a biometric personal identification method using static footprint features viz. friction ridge / texture and foot shape / silhouette. To begin with, naked footprints of users are captured; images then undergo pre processing followed by the extraction of two features; shape using Gradient Vector Flow (GVF) snake model and minutiae extraction respectively. Matching is then effected based on these two features followed by a fusion of these two results for either a reject or accept decision. Our shape matching feature is based on cosine similarity while the texture one is based on miniature score matching. The results from our research establish that the naked footprint is a credible biometric feature as two barefoot impressions of an individual match perfectly while that of two different persons shows a great deal of dissimilarity. Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Doi: 10.12777/ijse.5.2.29-35 How to cite this article: King

  18. Soft Biometrics; Human Identification Using Comparative Descriptions.

    Science.gov (United States)

    Reid, Daniel A; Nixon, Mark S; Stevenage, Sarah V

    2014-06-01

    Soft biometrics are a new form of biometric identification which use physical or behavioral traits that can be naturally described by humans. Unlike other biometric approaches, this allows identification based solely on verbal descriptions, bridging the semantic gap between biometrics and human description. To permit soft biometric identification the description must be accurate, yet conventional human descriptions comprising of absolute labels and estimations are often unreliable. A novel method of obtaining human descriptions will be introduced which utilizes comparative categorical labels to describe differences between subjects. This innovative approach has been shown to address many problems associated with absolute categorical labels-most critically, the descriptions contain more objective information and have increased discriminatory capabilities. Relative measurements of the subjects' traits can be inferred from comparative human descriptions using the Elo rating system. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate recognition of subjects. Relative measurements can also be obtained from other forms of human representation. This is demonstrated using a support vector machine to determine relative measurements from gait biometric signatures-allowing retrieval of subjects from video footage by using human comparisons, bridging the semantic gap.

  19. Evaluation of multimodal ground cues

    DEFF Research Database (Denmark)

    Nordahl, Rolf; Lecuyer, Anatole; Serafin, Stefania

    2012-01-01

    This chapter presents an array of results on the perception of ground surfaces via multiple sensory modalities,with special attention to non visual perceptual cues, notably those arising from audition and haptics, as well as interactions between them. It also reviews approaches to combining...... synthetic multimodal cues, from vision, haptics, and audition, in order to realize virtual experiences of walking on simulated ground surfaces or other features....

  20. Comparative analysis of the quality of biometric methods

    OpenAIRE

    Filipčík, Jan

    2010-01-01

    The main objective is to describe and analyze the types of biometric identification and selected biometric methods and identify their strengths and weaknesses compared to the current document type of identification and verification of persons and compared to other biometric methods and then focus on the relationships and support of biometric methods in terms of IS / ICT services. The work will consist of 5 types of biometric methods namely dactyloscopy, hand geometry scanning, facial scanning...

  1. Gaze Estimation for Off-Angle Iris Recognition Based on the Biometric Eye Model

    Energy Technology Data Exchange (ETDEWEB)

    Karakaya, Mahmut [ORNL; Barstow, Del R [ORNL; Santos-Villalobos, Hector J [ORNL; Thompson, Joseph W [ORNL; Bolme, David S [ORNL; Boehnen, Chris Bensing [ORNL

    2013-01-01

    Iris recognition is among the highest accuracy biometrics. However, its accuracy relies on controlled high quality capture data and is negatively affected by several factors such as angle, occlusion, and dilation. Non-ideal iris recognition is a new research focus in biometrics. In this paper, we present a gaze estimation method designed for use in an off-angle iris recognition framework based on the ANONYMIZED biometric eye model. Gaze estimation is an important prerequisite step to correct an off-angle iris images. To achieve the accurate frontal reconstruction of an off-angle iris image, we first need to estimate the eye gaze direction from elliptical features of an iris image. Typically additional information such as well-controlled light sources, head mounted equipment, and multiple cameras are not available. Our approach utilizes only the iris and pupil boundary segmentation allowing it to be applicable to all iris capture hardware. We compare the boundaries with a look-up-table generated by using our biologically inspired biometric eye model and find the closest feature point in the look-up-table to estimate the gaze. Based on the results from real images, the proposed method shows effectiveness in gaze estimation accuracy for our biometric eye model with an average error of approximately 3.5 degrees over a 50 degree range.

  2. Data Acquisition for Modular Biometric Monitoring System

    Science.gov (United States)

    Chmiel, Alan J. (Inventor); Humphreys, Bradley T. (Inventor); Grodsinsky, Carlos M. (Inventor)

    2014-01-01

    A modular system for acquiring biometric data includes a plurality of data acquisition modules configured to sample biometric data from at least one respective input channel at a data acquisition rate. A representation of the sampled biometric data is stored in memory of each of the plurality of data acquisition modules. A central control system is in communication with each of the plurality of data acquisition modules through a bus. The central control system is configured to collect data asynchronously, via the bus, from the memory of the plurality of data acquisition modules according to a relative fullness of the memory of the plurality of data acquisition modules.

  3. Biometric Systems Private by Design: Reasoning about privacy properties of biometric system architectures

    OpenAIRE

    Bringer, Julien; Chabanne, Herve; Metayer, Daniel Le; Lescuyer, Roch

    2017-01-01

    This work aims to show the applicability, and how, of privacy by design approach to biometric systems and the benefit of using formal methods to this end. Starting from a general framework that has been introduced at STM in 2014, that enables to define privacy architectures and to formally reason about their properties, we explain how it can be adapted to biometrics. The choice of particular techniques and the role of the components (central server, secure module, biometric terminal, smart ca...

  4. A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

    Science.gov (United States)

    Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

    2018-02-19

    The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

  5. The biometric antecedents to happiness.

    Directory of Open Access Journals (Sweden)

    Petri Böckerman

    Full Text Available It has been suggested that biological markers are associated with human happiness. We contribute to the empirical literature by examining the independent association between various aspects of biometric wellbeing measured in childhood and happiness in adulthood. Using Young Finns Study data (n = 1905 and nationally representative linked data we examine whether eight biomarkers measured in childhood (1980 are associated with happiness in adulthood (2001. Using linked data we account for a very rich set of confounders including age, sex, body size, family background, nutritional intake, physical activity, income, education and labour market experiences. We find that there is a negative relationship between triglycerides and subjective well-being but it is both gender- and age-specific and the relationship does not prevail using the later measurements (1983/1986 on triglycerides. In summary, we conclude that none of the eight biomarkers measured in childhood predict happiness robustly in adulthood.

  6. The biometric antecedents to happiness.

    Science.gov (United States)

    Böckerman, Petri; Bryson, Alex; Viinikainen, Jutta; Hakulinen, Christian; Hintsanen, Mirka; Pehkonen, Jaakko; Viikari, Jorma; Raitakari, Olli

    2017-01-01

    It has been suggested that biological markers are associated with human happiness. We contribute to the empirical literature by examining the independent association between various aspects of biometric wellbeing measured in childhood and happiness in adulthood. Using Young Finns Study data (n = 1905) and nationally representative linked data we examine whether eight biomarkers measured in childhood (1980) are associated with happiness in adulthood (2001). Using linked data we account for a very rich set of confounders including age, sex, body size, family background, nutritional intake, physical activity, income, education and labour market experiences. We find that there is a negative relationship between triglycerides and subjective well-being but it is both gender- and age-specific and the relationship does not prevail using the later measurements (1983/1986) on triglycerides. In summary, we conclude that none of the eight biomarkers measured in childhood predict happiness robustly in adulthood.

  7. A Vein Map Biometric System

    Directory of Open Access Journals (Sweden)

    Felix Fuentes

    2013-08-01

    Full Text Available There is increasing demand world-wide, from government agencies and the private sector for cutting-edge biometric security technology that is difficult to breach but userfriendly at the same time. Some of the older tools, such as fingerprint, retina and iris scanning, and facial recognition software have all been found to have flaws and often viewed negatively because of many cultural and hygienic issues associated with them. Comparatively, mapping veins as a human barcode, a new technology, has many advantages over older technologies. Specifically, reproducing a three-dimensional model of a human vein system is impossible to replicate. Vein map technology is distinctive because of its state-of-the-art sensors are only able to recognize vein patterns if hemoglobin is actively flowing through the person

  8. Performance of biometric quality measures.

    Science.gov (United States)

    Grother, Patrick; Tabassi, Elham

    2007-04-01

    We document methods for the quantitative evaluation of systems that produce a scalar summary of a biometric sample's quality. We are motivated by a need to test claims that quality measures are predictive of matching performance. We regard a quality measurement algorithm as a black box that converts an input sample to an output scalar. We evaluate it by quantifying the association between those values and observed matching results. We advance detection error trade-off and error versus reject characteristics as metrics for the comparative evaluation of sample quality measurement algorithms. We proceed this with a definition of sample quality, a description of the operational use of quality measures. We emphasize the performance goal by including a procedure for annotating the samples of a reference corpus with quality values derived from empirical recognition scores.

  9. THRIVE: threshold homomorphic encryption based secure and privacy preserving biometric verification system

    Science.gov (United States)

    Karabat, Cagatay; Kiraz, Mehmet Sabir; Erdogan, Hakan; Savas, Erkay

    2015-12-01

    In this paper, we introduce a new biometric verification and template protection system which we call THRIVE. The system includes novel enrollment and authentication protocols based on threshold homomorphic encryption where a private key is shared between a user and a verifier. In the THRIVE system, only encrypted binary biometric templates are stored in a database and verification is performed via homomorphically randomized templates, thus, original templates are never revealed during authentication. Due to the underlying threshold homomorphic encryption scheme, a malicious database owner cannot perform full decryption on encrypted templates of the users in the database. In addition, security of the THRIVE system is enhanced using a two-factor authentication scheme involving user's private key and biometric data. Using simulation-based techniques, the proposed system is proven secure in the malicious model. The proposed system is suitable for applications where the user does not want to reveal her biometrics to the verifier in plain form, but needs to prove her identity by using biometrics. The system can be used with any biometric modality where a feature extraction method yields a fixed size binary template and a query template is verified when its Hamming distance to the database template is less than a threshold. The overall connection time for the proposed THRIVE system is estimated to be 336 ms on average for 256-bit biometric templates on a desktop PC running with quad core 3.2 GHz CPUs at 10 Mbit/s up/down link connection speed. Consequently, the proposed system can be efficiently used in real-life applications.

  10. Compressed sensing approach for wrist vein biometrics.

    Science.gov (United States)

    Lantsov, Aleksey; Ryabko, Maxim; Shchekin, Aleksey

    2018-04-01

    The work describes features of the compressed sensing (CS) approach utilized for development of a wearable system for wrist vein recognition with single-pixel detection; we consider this system useful for biometrics authentication purposes. The CS approach implies use of a spatial light modulation (SLM) which, in our case, can be performed differently-with a liquid crystal display or diffusely scattering medium. We show that compressed sensing combined with above-mentioned means of SLM allows us to avoid using an optical system-a limiting factor for wearable devices. The trade-off between the 2 different SLM approaches regarding issues of practical implementation of CS approach for wrist vein recognition purposes is discussed. A possible solution of a misalignment problem-a typical issue for imaging systems based upon 2D arrays of photodiodes-is also proposed. Proposed design of the wearable device for wrist vein recognition is based upon single-pixel detection. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Update on the US Government's Biometric Consortium

    National Research Council Canada - National Science Library

    Campbell, Joseph

    1997-01-01

    .... The goals of the consortium remain largely the same under this new leadership. The current emphasis is on the formal approval of our charter and on the establishment of a national biometric test and evaluation laboratory.

  12. Autopoietic Theory as a Framework for Biometrics

    Directory of Open Access Journals (Sweden)

    Markus Schatten

    2009-01-01

    Full Text Available Autopoietic theory which represents a framework for describing complex non-linear and especially living systems is described in a context of biometric characteristics. It is argued that any living system by performing an internal process of reproducing its structural components yields physical biometric characteristics. Likewise any living system when structurally coupling to another (eventually allopoietic system yields a behavioral or psychological characteristic of the living system. It is shown that any system that can be considered as autopoietic can potentially be measured, authenticated and/or identified using adequate biometric methods, and thus biometrics is applicable to any autopoietic system: living beings, groups of living beings, social systems, organizations as well as information systems. In the end implications of such a conceptualization are discussed as well as possible applications.

  13. Voice Biometrics for Information Assurance Applications

    National Research Council Canada - National Science Library

    Kang, George

    2002-01-01

    In 2002, the President of the United States established an organization within the DOD to develop and promulgate biometrics technologies to achieve security in information, information systems, weapons, and facilities...

  14. Challenges at different stages of an iris based biometric system

    Directory of Open Access Journals (Sweden)

    Sunil Kumar Singla

    2012-04-01

    Full Text Available Iris recognition has been used for authentication for the past few years and is capable of positive/negative authenticationof an individual without any physical contact or intervention. This technique is being used mainly because of its uniqueness,stability, and reliability but still many challenges are being faced an the iris based recognition system. This paperpresents the difficulties faced in different modules, like the sensor module, preprocessing module, feature extraction module,and matching module of an iris biometric system.

  15. BioTwist: overcoming severe distortions in ridge-based biometrics for successful identification

    NARCIS (Netherlands)

    Kotzerke, Johannes

    2016-01-01

    Biometrics rely on a physical trait's permanence and stability over time, as well as its individuality, robustness and ease to be captured. Challenges arise when working with newborns or infants because of the tininess and fragility of an infant's features, their uncooperative nature and their rapid

  16. An EEG-Based Biometric System Using Eigenvector Centrality in Resting State Brain Networks

    NARCIS (Netherlands)

    Fraschini, M.; Hillebrand, A.; Demuru, M.; Didaci, L.; Marcialis, G.L.

    2015-01-01

    Recently, there has been a growing interest in the use of brain activity for biometric systems. However, so far these studies have focused mainly on basic features of the Electroencephalography. In this study we propose an approach based on phase synchronization, to investigate personal distinctive

  17. Biometrics IRB best practices and data protection

    Science.gov (United States)

    Boehnen, Christopher; Bolme, David; Flynn, Patrick

    2015-05-01

    The collection of data from human subjects for biometrics research in the United States requires the development of a data collection protocol that is reviewed by a Human Subjects Institutional Review Board (IRB). The IRB reviews the protocol for risks and approves it if it meets the criteria for approval specified in the relevant Federal regulations (45 CFR 46). Many other countries operate similar mechanisms for the protection of human subjects. IRBs review protocols for safety, confidentiality, and for minimization of risk associated with identity disclosure. Since biometric measurements are potentially identifying, IRB scrutiny of biometrics data collection protocols can be expected to be thorough. This paper discusses the intricacies of IRB best practices within the worldwide biometrics community. This is important because research decisions involving human subjects are made at a local level and do not set a precedent for decisions made by another IRB board. In many cases, what one board approves is not approved by another board, resulting in significant inconsistencies that prove detrimental to both researchers and human subjects. Furthermore, the level of biometrics expertise may be low on IRBs, which can contribute to the unevenness of reviews. This publication will suggest possible best practices for designing and seeking IRB approval for human subjects research involving biometrics measurements. The views expressed are the opinions of the authors.

  18. Crop Biometric Maps: The Key to Prediction

    Directory of Open Access Journals (Sweden)

    Francisco Rovira-Más

    2013-09-01

    Full Text Available The sustainability of agricultural production in the twenty-first century, both in industrialized and developing countries, benefits from the integration of farm management with information technology such that individual plants, rows, or subfields may be endowed with a singular “identity.” This approach approximates the nature of agricultural processes to the engineering of industrial processes. In order to cope with the vast variability of nature and the uncertainties of agricultural production, the concept of crop biometrics is defined as the scientific analysis of agricultural observations confined to spaces of reduced dimensions and known position with the purpose of building prediction models. This article develops the idea of crop biometrics by setting its principles, discussing the selection and quantization of biometric traits, and analyzing the mathematical relationships among measured and predicted traits. Crop biometric maps were applied to the case of a wine-production vineyard, in which vegetation amount, relative altitude in the field, soil compaction, berry size, grape yield, juice pH, and grape sugar content were selected as biometric traits. The enological potential of grapes was assessed with a quality-index map defined as a combination of titratable acidity, sugar content, and must pH. Prediction models for yield and quality were developed for high and low resolution maps, showing the great potential of crop biometric maps as a strategic tool for vineyard growers as well as for crop managers in general, due to the wide versatility of the methodology proposed.

  19. A STUDY ON BIOMETRIC TEMPLATE SECURITY

    Directory of Open Access Journals (Sweden)

    N. Radha

    2010-07-01

    Full Text Available The increasing popularity of biometrics and cryptography is driven by the widespread stipulation on information security. Abundant efforts have been made in developing successful methods in these areas in order to accomplish an enhanced level of information security. There are two dominant issues in information security enhancement. One is to defend the user ownership and control the access to information by authenticating an individual’s identity. The other is to make sure the privacy and integrity of information and to secure communication. Cryptography is the science of writing in secret code. Secret-key cryptography and public-key cryptography are the two most important cryptographic architectures. The security of a cryptographic system is reliant on the secrecy of the cryptographic key. Biometric authentication or simply biometrics refers to establishing automatic personal recognition based on the physical and behavioral characteristics of an individual (e.g. face, voice, fingerprint, gait, hand geometry, iris, gene, etc.. Biometrics offers superior security and easier than traditional identity authentication systems (based on passwords and cryptographic keys.Since biometrics characteristics are naturally related with a particular individual, making them insusceptible to being stolen, forgotten, lost or attached. This paper presents a survey on various techniques proposed earlier in developing an authentication system for ensuring individual’s information security by combining biometric characteristics of that particular individual and the cryptographic techniques. In addition, it provides some fundamental idea for future research that may help in eliminating the problems associated with the present authentication systems.

  20. Crop biometric maps: the key to prediction.

    Science.gov (United States)

    Rovira-Más, Francisco; Sáiz-Rubio, Verónica

    2013-09-23

    The sustainability of agricultural production in the twenty-first century, both in industrialized and developing countries, benefits from the integration of farm management with information technology such that individual plants, rows, or subfields may be endowed with a singular "identity." This approach approximates the nature of agricultural processes to the engineering of industrial processes. In order to cope with the vast variability of nature and the uncertainties of agricultural production, the concept of crop biometrics is defined as the scientific analysis of agricultural observations confined to spaces of reduced dimensions and known position with the purpose of building prediction models. This article develops the idea of crop biometrics by setting its principles, discussing the selection and quantization of biometric traits, and analyzing the mathematical relationships among measured and predicted traits. Crop biometric maps were applied to the case of a wine-production vineyard, in which vegetation amount, relative altitude in the field, soil compaction, berry size, grape yield, juice pH, and grape sugar content were selected as biometric traits. The enological potential of grapes was assessed with a quality-index map defined as a combination of titratable acidity, sugar content, and must pH. Prediction models for yield and quality were developed for high and low resolution maps, showing the great potential of crop biometric maps as a strategic tool for vineyard growers as well as for crop managers in general, due to the wide versatility of the methodology proposed.

  1. Normalizing Electrocardiograms of Both Healthy Persons and Cardiovascular Disease Patients for Biometric Authentication

    Science.gov (United States)

    Zhao, Miaomiao; Li, Fan; Wang, Guoqing; Zhou, Fengfeng

    2013-01-01

    Although electrocardiogram (ECG) fluctuates over time and physical activity, some of its intrinsic measurements serve well as biometric features. Considering its constant availability and difficulty in being faked, the ECG signal is becoming a promising factor for biometric authentication. The majority of the currently available algorithms only work well on healthy participants. A novel normalization and interpolation algorithm is proposed to convert an ECG signal into multiple template cycles, which are comparable between any two ECGs, no matter the sampling rates or health status. The overall accuracies reach 100% and 90.11% for healthy participants and cardiovascular disease (CVD) patients, respectively. PMID:23977063

  2. A new Watermarking System based on Discrete Cosine Transform (DCT) in color biometric images.

    Science.gov (United States)

    Dogan, Sengul; Tuncer, Turker; Avci, Engin; Gulten, Arif

    2012-08-01

    This paper recommend a biometric color images hiding approach An Watermarking System based on Discrete Cosine Transform (DCT), which is used to protect the security and integrity of transmitted biometric color images. Watermarking is a very important hiding information (audio, video, color image, gray image) technique. It is commonly used on digital objects together with the developing technology in the last few years. One of the common methods used for hiding information on image files is DCT method which used in the frequency domain. In this study, DCT methods in order to embed watermark data into face images, without corrupting their features.

  3. Biometrics based key management of double random phase encoding scheme using error control codes

    Science.gov (United States)

    Saini, Nirmala; Sinha, Aloka

    2013-08-01

    In this paper, an optical security system has been proposed in which key of the double random phase encoding technique is linked to the biometrics of the user to make it user specific. The error in recognition due to the biometric variation is corrected by encoding the key using the BCH code. A user specific shuffling key is used to increase the separation between genuine and impostor Hamming distance distribution. This shuffling key is then further secured using the RSA public key encryption to enhance the security of the system. XOR operation is performed between the encoded key and the feature vector obtained from the biometrics. The RSA encoded shuffling key and the data obtained from the XOR operation are stored into a token. The main advantage of the present technique is that the key retrieval is possible only in the simultaneous presence of the token and the biometrics of the user which not only authenticates the presence of the original input but also secures the key of the system. Computational experiments showed the effectiveness of the proposed technique for key retrieval in the decryption process by using the live biometrics of the user.

  4. Cryptanalysis and Improvement of a Biometric-Based Multi-Server Authentication and Key Agreement Scheme.

    Directory of Open Access Journals (Sweden)

    Chengqi Wang

    Full Text Available With the security requirements of networks, biometrics authenticated schemes which are applied in the multi-server environment come to be more crucial and widely deployed. In this paper, we propose a novel biometric-based multi-server authentication and key agreement scheme which is based on the cryptanalysis of Mishra et al.'s scheme. The informal and formal security analysis of our scheme are given, which demonstrate that our scheme satisfies the desirable security requirements. The presented scheme provides a variety of significant functionalities, in which some features are not considered in the most of existing authentication schemes, such as, user revocation or re-registration and biometric information protection. Compared with several related schemes, our scheme has more secure properties and lower computation cost. It is obviously more appropriate for practical applications in the remote distributed networks.

  5. Cryptanalysis and Improvement of a Biometric-Based Multi-Server Authentication and Key Agreement Scheme

    Science.gov (United States)

    Wang, Chengqi; Zhang, Xiao; Zheng, Zhiming

    2016-01-01

    With the security requirements of networks, biometrics authenticated schemes which are applied in the multi-server environment come to be more crucial and widely deployed. In this paper, we propose a novel biometric-based multi-server authentication and key agreement scheme which is based on the cryptanalysis of Mishra et al.’s scheme. The informal and formal security analysis of our scheme are given, which demonstrate that our scheme satisfies the desirable security requirements. The presented scheme provides a variety of significant functionalities, in which some features are not considered in the most of existing authentication schemes, such as, user revocation or re-registration and biometric information protection. Compared with several related schemes, our scheme has more secure properties and lower computation cost. It is obviously more appropriate for practical applications in the remote distributed networks. PMID:26866606

  6. Cryptanalysis and Improvement of a Biometric-Based Multi-Server Authentication and Key Agreement Scheme.

    Science.gov (United States)

    Wang, Chengqi; Zhang, Xiao; Zheng, Zhiming

    2016-01-01

    With the security requirements of networks, biometrics authenticated schemes which are applied in the multi-server environment come to be more crucial and widely deployed. In this paper, we propose a novel biometric-based multi-server authentication and key agreement scheme which is based on the cryptanalysis of Mishra et al.'s scheme. The informal and formal security analysis of our scheme are given, which demonstrate that our scheme satisfies the desirable security requirements. The presented scheme provides a variety of significant functionalities, in which some features are not considered in the most of existing authentication schemes, such as, user revocation or re-registration and biometric information protection. Compared with several related schemes, our scheme has more secure properties and lower computation cost. It is obviously more appropriate for practical applications in the remote distributed networks.

  7. Performance evaluation of no-reference image quality metrics for face biometric images

    Science.gov (United States)

    Liu, Xinwei; Pedersen, Marius; Charrier, Christophe; Bours, Patrick

    2018-03-01

    The accuracy of face recognition systems is significantly affected by the quality of face sample images. The recent established standardization proposed several important aspects for the assessment of face sample quality. There are many existing no-reference image quality metrics (IQMs) that are able to assess natural image quality by taking into account similar image-based quality attributes as introduced in the standardization. However, whether such metrics can assess face sample quality is rarely considered. We evaluate the performance of 13 selected no-reference IQMs on face biometrics. The experimental results show that several of them can assess face sample quality according to the system performance. We also analyze the strengths and weaknesses of different IQMs as well as why some of them failed to assess face sample quality. Retraining an original IQM by using face database can improve the performance of such a metric. In addition, the contribution of this paper can be used for the evaluation of IQMs on other biometric modalities; furthermore, it can be used for the development of multimodality biometric IQMs.

  8. The relation between the secrecy rate of biometric template protection and biometric recognition performance

    NARCIS (Netherlands)

    Veldhuis, Raymond N.J.

    2015-01-01

    A theoretical result relating the maximum achievable security of the family of biometric template protection systems known as key-binding systems to the recognition performance of a biometric recognition system that is optimal in Neyman-Pearson sense is derived. The relation allows for the

  9. Modelling of Biometric Identification System with Given Parameters Using Colored Petri Nets

    Science.gov (United States)

    Petrosyan, G.; Ter-Vardanyan, L.; Gaboutchian, A.

    2017-05-01

    Biometric identification systems use given parameters and function on the basis of Colored Petri Nets as a modelling language developed for systems in which communication, synchronization and distributed resources play an important role. Colored Petri Nets combine the strengths of Classical Petri Nets with the power of a high-level programming language. Coloured Petri Nets have both, formal intuitive and graphical presentations. Graphical CPN model consists of a set of interacting modules which include a network of places, transitions and arcs. Mathematical representation has a well-defined syntax and semantics, as well as defines system behavioural properties. One of the best known features used in biometric is the human finger print pattern. During the last decade other human features have become of interest, such as iris-based or face recognition. The objective of this paper is to introduce the fundamental concepts of Petri Nets in relation to tooth shape analysis. Biometric identification systems functioning has two phases: data enrollment phase and identification phase. During the data enrollment phase images of teeth are added to database. This record contains enrollment data as a noisy version of the biometrical data corresponding to the individual. During the identification phase an unknown individual is observed again and is compared to the enrollment data in the database and then system estimates the individual. The purpose of modeling biometric identification system by means of Petri Nets is to reveal the following aspects of the functioning model: the efficiency of the model, behavior of the model, mistakes and accidents in the model, feasibility of the model simplification or substitution of its separate components for more effective components without interfering system functioning. The results of biometric identification system modeling and evaluating are presented and discussed.

  10. Ethnicity distinctiveness through iris texture features using Gabor filters

    CSIR Research Space (South Africa)

    Mabuza-Hocquet, Gugulethu P

    2017-02-01

    Full Text Available Research in iris biometrics has been focused on utilizing iris features as a means of identity verification and authentication. However, not enough research work has been done to explore iris textures to determine soft biometrics such as gender...

  11. Cardiac imaging. A multimodality approach

    Energy Technology Data Exchange (ETDEWEB)

    Thelen, Manfred [Johannes Gutenberg University Hospital, Mainz (Germany); Erbel, Raimund [University Hospital Essen (Germany). Dept. of Cardiology; Kreitner, Karl-Friedrich [Johannes Gutenberg University Hospital, Mainz (Germany). Clinic and Polyclinic for Diagnostic and Interventional Radiology; Barkhausen, Joerg (eds.) [University Hospital Schleswig-Holstein, Luebeck (Germany). Dept. of Radiology and Nuclear Medicine

    2009-07-01

    An excellent atlas on modern diagnostic imaging of the heart Written by an interdisciplinary team of experts, Cardiac Imaging: A Multimodality Approach features an in-depth introduction to all current imaging modalities for the diagnostic assessment of the heart as well as a clinical overview of cardiac diseases and main indications for cardiac imaging. With a particular emphasis on CT and MRI, the first part of the atlas also covers conventional radiography, echocardiography, angiography and nuclear medicine imaging. Leading specialists demonstrate the latest advances in the field, and compare the strengths and weaknesses of each modality. The book's second part features clinical chapters on heart defects, endocarditis, coronary heart disease, cardiomyopathies, myocarditis, cardiac tumors, pericardial diseases, pulmonary vascular diseases, and diseases of the thoracic aorta. The authors address anatomy, pathophysiology, and clinical features, and evaluate the various diagnostic options. Key features: - Highly regarded experts in cardiology and radiology off er image-based teaching of the latest techniques - Readers learn how to decide which modality to use for which indication - Visually highlighted tables and essential points allow for easy navigation through the text - More than 600 outstanding images show up-to-date technology and current imaging protocols Cardiac Imaging: A Multimodality Approach is a must-have desk reference for cardiologists and radiologists in practice, as well as a study guide for residents in both fields. It will also appeal to cardiac surgeons, general practitioners, and medical physicists with a special interest in imaging of the heart. (orig.)

  12. Cardiac imaging. A multimodality approach

    International Nuclear Information System (INIS)

    Thelen, Manfred; Erbel, Raimund; Kreitner, Karl-Friedrich; Barkhausen, Joerg

    2009-01-01

    An excellent atlas on modern diagnostic imaging of the heart Written by an interdisciplinary team of experts, Cardiac Imaging: A Multimodality Approach features an in-depth introduction to all current imaging modalities for the diagnostic assessment of the heart as well as a clinical overview of cardiac diseases and main indications for cardiac imaging. With a particular emphasis on CT and MRI, the first part of the atlas also covers conventional radiography, echocardiography, angiography and nuclear medicine imaging. Leading specialists demonstrate the latest advances in the field, and compare the strengths and weaknesses of each modality. The book's second part features clinical chapters on heart defects, endocarditis, coronary heart disease, cardiomyopathies, myocarditis, cardiac tumors, pericardial diseases, pulmonary vascular diseases, and diseases of the thoracic aorta. The authors address anatomy, pathophysiology, and clinical features, and evaluate the various diagnostic options. Key features: - Highly regarded experts in cardiology and radiology off er image-based teaching of the latest techniques - Readers learn how to decide which modality to use for which indication - Visually highlighted tables and essential points allow for easy navigation through the text - More than 600 outstanding images show up-to-date technology and current imaging protocols Cardiac Imaging: A Multimodality Approach is a must-have desk reference for cardiologists and radiologists in practice, as well as a study guide for residents in both fields. It will also appeal to cardiac surgeons, general practitioners, and medical physicists with a special interest in imaging of the heart. (orig.)

  13. Biometric identification using infrared dorsum hand vein images

    Directory of Open Access Journals (Sweden)

    Óscar Fernando Motato Toro

    2009-01-01

    Full Text Available The evident need for improving access and safety controls has orientated the development of new personal identification systems towards using biometric, physiological and behavioral features guaranteeing increasing greater levels of performance. Motivated by this trend, the development and implementation of a computational tool for recording and validating people’s identity using dorsum hand vein images is presented here. A low-cost hardware module for acquiring infrared images was thus designed; it consisted of a conventional video-camera, optical lenses, controlled infrared illumination sources and a frame grabber. The accompanying software module was concerned with visualizing and capturing images, selecting regions of interest, pattern seg-mentation in the region and extracting, describing and classifying these features. An artificial neuron network approach was im-plemented for pattern recognition, resulting in it proving the biometric indicator to be sufficiently discriminating, and a corre-lation-based approach using a 100 image database for static characterisation, determined the system’s maximum efficiency to be 95.72% at a threshold equal to 65. False acceptance rate (FAR was 8.57% and false rejection rate (FRR was 0% at this threshold.

  14. Biometrics in support of special forces medical operations.

    Science.gov (United States)

    Kershner, Michael R

    2012-01-01

    Recommendations on ways in which the ODA can leverage biometrics in medical operations to improve their security, improve relations with indigenous personnel, and contribute to the larger theater biometrics program. 2012.

  15. Review of modern biometric user authentication and their development prospects

    Science.gov (United States)

    Boriev, Z. V.; Sokolov, S. S.; Nyrkov, A. P.

    2015-09-01

    This article discusses the possibility of using biometric information technologies in management. Made a brief overview of access control and time attendance. Analyzed biometrics and identification system user. Recommendations on the use of various systems depending on the specific tasks.

  16. Application of Some Biometric Indices in the Assessment of the ...

    African Journals Online (AJOL)

    Application of Some Biometric Indices in the Assessment of the Water Quality of the Benin River, Niger Delta, Nigeria. ... Username, Password, Remember me, or Register ... Rapid Bioassessment Protocols (RBP) using some biometric indices ...

  17. Multimodality imaging of pulmonary infarction

    International Nuclear Information System (INIS)

    Bray, T.J.P.; Mortensen, K.H.; Gopalan, D.

    2014-01-01

    Highlights: • A plethora of pulmonary and systemic disorders, often associated with grave outcomes, may cause pulmonary infarction. • A stereotypical infarct is a peripheral wedge shaped pleurally based opacity but imaging findings can be highly variable. • Multimodality imaging is key to diagnosing the presence, aetiology and complications of pulmonary infarction. • Multimodality imaging of pulmonary infarction together with any ancillary features often guide to early targeted treatment. • CT remains the principal imaging modality with MRI increasingly used alongside nuclear medicine studies and ultrasound. - Abstract: The impact of absent pulmonary arterial and venous flow on the pulmonary parenchyma depends on a host of factors. These include location of the occlusive insult, the speed at which the occlusion develops and the ability of the normal dual arterial supply to compensate through increased bronchial arterial flow. Pulmonary infarction occurs when oxygenation is cut off secondary to sudden occlusion with lack of recruitment of the dual supply arterial system. Thromboembolic disease is the commonest cause of such an insult but a whole range of disease processes intrinsic and extrinsic to the pulmonary arterial and venous lumen may also result in infarcts. Recognition of the presence of infarction can be challenging as imaging manifestations often differ from the classically described wedge shaped defect and a number of weighty causes need consideration. This review highlights aetiologies and imaging appearances of pulmonary infarction, utilising cases to illustrate the essential role of a multimodality imaging approach in order to arrive at the appropriate diagnosis

  18. Multimodality imaging of pulmonary infarction

    Energy Technology Data Exchange (ETDEWEB)

    Bray, T.J.P., E-mail: timothyjpbray@gmail.com [Department of Radiology, Papworth Hospital NHS Foundation Trust, Ermine Street, Papworth Everard, Cambridge CB23 3RE (United Kingdom); Mortensen, K.H., E-mail: mortensen@doctors.org.uk [Department of Radiology, Papworth Hospital NHS Foundation Trust, Ermine Street, Papworth Everard, Cambridge CB23 3RE (United Kingdom); University Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Box 318, Cambridge CB2 0QQ (United Kingdom); Gopalan, D., E-mail: deepa.gopalan@btopenworld.com [Department of Radiology, Papworth Hospital NHS Foundation Trust, Ermine Street, Papworth Everard, Cambridge CB23 3RE (United Kingdom)

    2014-12-15

    Highlights: • A plethora of pulmonary and systemic disorders, often associated with grave outcomes, may cause pulmonary infarction. • A stereotypical infarct is a peripheral wedge shaped pleurally based opacity but imaging findings can be highly variable. • Multimodality imaging is key to diagnosing the presence, aetiology and complications of pulmonary infarction. • Multimodality imaging of pulmonary infarction together with any ancillary features often guide to early targeted treatment. • CT remains the principal imaging modality with MRI increasingly used alongside nuclear medicine studies and ultrasound. - Abstract: The impact of absent pulmonary arterial and venous flow on the pulmonary parenchyma depends on a host of factors. These include location of the occlusive insult, the speed at which the occlusion develops and the ability of the normal dual arterial supply to compensate through increased bronchial arterial flow. Pulmonary infarction occurs when oxygenation is cut off secondary to sudden occlusion with lack of recruitment of the dual supply arterial system. Thromboembolic disease is the commonest cause of such an insult but a whole range of disease processes intrinsic and extrinsic to the pulmonary arterial and venous lumen may also result in infarcts. Recognition of the presence of infarction can be challenging as imaging manifestations often differ from the classically described wedge shaped defect and a number of weighty causes need consideration. This review highlights aetiologies and imaging appearances of pulmonary infarction, utilising cases to illustrate the essential role of a multimodality imaging approach in order to arrive at the appropriate diagnosis.

  19. The ocular biometric differences of diabetic patients.

    Science.gov (United States)

    Kocatürk, Tolga; Zengin, Mehmet Özgür; Cakmak, Harun; Evliçoglu, Gökhan Evren; Dündar, Sema Oruç; Omürlü, Imran Kurt; Unübol, Mustafa; Güney, Engin

    2014-01-01

    To investigate the differences in ocular biometric and keratometric characteristics in comparison with biometric measurements using the noncontact optical low coherence reflectometer (OLCR) (Lenstar LS 900, Haag-Streit) on diabetic patients. The eyes of 170 patients were included in this study, including 81 diabetic and 89 nondiabetic subjects. Optical biometric measurements of diabetic and nondiabetic patients (between the ages of 25 and 85 years) who applied to the ophthalmology clinic were noted from March to June 2013. Detailed ophthalmologic examinations were done for every subject. Biometric measurements were done using the noncontact OLCR device. Patient age ranged from 29 to 83 years. Subgroup analyses were done in diabetic patients according to their Hba1C levels. The minimum Hba1C value was 5.3, maximum was 12.4, and mean was 7.56 ± 1.48. The median duration of diabetes was 5 years (25th-75th percentile 3.00-11.75). Diabetic patients were found to have thicker lens and shallower anterior chamber in both eyes compared to nondiabetic control subjects. There were no statistical differences between the groups according to central corneal thickness, axial length, or keratometric values in both eyes. However, lens thicknesses were found to be thicker and anterior chamber depth values were found to be shallower in the diabetic group in both eyes. It may useful to determine eyeglasses prescription, refractive surgery calculation, lens selection, and previous cataract surgery according to biometric measurements after the regulation of blood glucose.

  20. Entropy Measurement for Biometric Verification Systems.

    Science.gov (United States)

    Lim, Meng-Hui; Yuen, Pong C

    2016-05-01

    Biometric verification systems are designed to accept multiple similar biometric measurements per user due to inherent intrauser variations in the biometric data. This is important to preserve reasonable acceptance rate of genuine queries and the overall feasibility of the recognition system. However, such acceptance of multiple similar measurements decreases the imposter's difficulty of obtaining a system-acceptable measurement, thus resulting in a degraded security level. This deteriorated security needs to be measurable to provide truthful security assurance to the users. Entropy is a standard measure of security. However, the entropy formula is applicable only when there is a single acceptable possibility. In this paper, we develop an entropy-measuring model for biometric systems that accepts multiple similar measurements per user. Based on the idea of guessing entropy, the proposed model quantifies biometric system security in terms of adversarial guessing effort for two practical attacks. Excellent agreement between analytic and experimental simulation-based measurement results on a synthetic and a benchmark face dataset justify the correctness of our model and thus the feasibility of the proposed entropy-measuring approach.

  1. Corneal topography measurements for biometric applications

    Science.gov (United States)

    Lewis, Nathan D.

    The term biometrics is used to describe the process of analyzing biological and behavioral traits that are unique to an individual in order to confirm or determine his or her identity. Many biometric modalities are currently being researched and implemented including, fingerprints, hand and facial geometry, iris recognition, vein structure recognition, gait, voice recognition, etc... This project explores the possibility of using corneal topography measurements as a trait for biometric identification. Two new corneal topographers were developed for this study. The first was designed to function as an operator-free device that will allow a user to approach the device and have his or her corneal topography measured. Human subject topography data were collected with this device and compared to measurements made with the commercially available Keratron Piccolo topographer (Optikon, Rome, Italy). A third topographer that departs from the standard Placido disk technology allows for arbitrary pattern illumination through the use of LCD monitors. This topographer was built and tested to be used in future research studies. Topography data was collected from 59 subjects and modeled using Zernike polynomials, which provide for a simple method of compressing topography data and comparing one topographical measurement with a database for biometric identification. The data were analyzed to determine the biometric error rates associated with corneal topography measurements. Reasonably accurate results, between three to eight percent simultaneous false match and false non-match rates, were achieved.

  2. Multimodal fluorescence imaging spectroscopy

    NARCIS (Netherlands)

    Stopel, Martijn H W; Blum, Christian; Subramaniam, Vinod; Engelborghs, Yves; Visser, Anthonie J.W.G.

    2014-01-01

    Multimodal fluorescence imaging is a versatile method that has a wide application range from biological studies to materials science. Typical observables in multimodal fluorescence imaging are intensity, lifetime, excitation, and emission spectra which are recorded at chosen locations at the sample.

  3. Multimodality in organization studies

    DEFF Research Database (Denmark)

    Van Leeuwen, Theo

    2017-01-01

    This afterword reviews the chapters in this volume and reflects on the synergies between organization and management studies and multimodality studies that emerge from the volume. These include the combination of strong sociological theorizing and detailed multimodal analysis, a focus on material...

  4. Biometrics Enabling Capability Increment 1 (BEC Inc 1)

    Science.gov (United States)

    2016-03-01

    modal biometrics submissions to include iris, face, palm and finger prints from biometrics collection devices, which will support the Warfighter in...2016 Major Automated Information System Annual Report Biometrics Enabling Capability Increment 1 (BEC Inc 1) Defense Acquisition Management...Phone: 227-3119 DSN Fax: Date Assigned: July 15, 2015 Program Information Program Name Biometrics Enabling Capability Increment 1 (BEC Inc 1) DoD

  5. Biometric Passport Validation Scheme using Radio Frequency Identification

    OpenAIRE

    V.K. Narendira Kumar; B. Srinivasan

    2013-01-01

    Biometric passports issued nowadays have an embedded RFID chip that carries digitally signed biometric information. This RIFD chip is integrated into the cover of a passport, called a biometric passport. Electronic passports as it is sometimes called, represents a bold initiative in the deployment of two new technologies: RIFD and biometrics such as face, fingerprints, palm prints and iris. The electronic passport is the privacy and security risks that arise by embedding RFID technology. The ...

  6. Multi-biometrics based cryptographic key regeneration scheme

    OpenAIRE

    Kanade , Sanjay Ganesh; Petrovska-Delacrétaz , Dijana; Dorizzi , Bernadette

    2009-01-01

    International audience; Biometrics lack revocability and privacy while cryptography cannot detect the user's identity. By obtaining cryptographic keys using biometrics, one can achieve the properties such as revocability, assurance about user's identity, and privacy. In this paper, we propose a multi-biometric based cryptographic key regeneration scheme. Since left and right irises of a person are uncorrelated, we treat them as two independent biometrics and combine in our system. We propose ...

  7. Authentication: From Passwords to Biometrics: An implementation of a speaker recognition system on Android

    OpenAIRE

    Heimark, Erlend

    2012-01-01

    We implement a biometric authentication system on the Android platform, which is based on text-dependent speaker recognition. The Android version used in the application is Android 4.0. The application makes use of the Modular Audio Recognition Framework, from which many of the algorithms are adapted in the processes of preprocessing and feature extraction. In addition, we employ the Dynamic Time Warping (DTW) algorithm for the comparison of different voice features. A training procedure is i...

  8. Biometrics and their use in e-passports

    NARCIS (Netherlands)

    Schouten, B.A.M.; Jacobs, B.P.F.

    2009-01-01

    A successful design, deployment and operation of biometric systems depends highly on the results for existing biometrical technologies and components. These existing technologies as well as new solutions need to be evaluated on their performance. However it is often forgotten that the biometric

  9. Biometrics and their use in e-passports

    NARCIS (Netherlands)

    Prof. Bart Jacobs; B.A.M. Ben Schouten

    2007-01-01

    A succesful design, deployment and operation of biometric systems depends highly on the results for existing biometrical technologies and components. These existing technologies as well as new solutions need to be evaluated on their performance. However it is often forgotten that the biometric

  10. Biometrics in Forensic Science: Challenges, Lessons and New Technologies

    NARCIS (Netherlands)

    Tistarelli, Massimo; Grosso, Enrico; Meuwly, Didier

    2014-01-01

    Biometrics has historically found its natural mate in Forensics. The first applications found in the literature and over cited so many times, are related to biometric measurements for the identification of multiple offenders from some of their biometric and anthropometric characteristics (tenprint

  11. 75 FR 39323 - Amendment to the Biometric Visa Program

    Science.gov (United States)

    2010-07-08

    ... DEPARTMENT OF STATE [Public Notice: 7047] Amendment to the Biometric Visa Program AGENCY: Department of State. ACTION: Notice of Amendment to the Biometric Visa Program. This public notice announces an amendment to the Biometric Visa Program. Section 303 of the Enhanced Border Security and Visa...

  12. Secret-key rates and privacy leakage in biometric systems

    NARCIS (Netherlands)

    Ignatenko, T.

    2009-01-01

    In this thesis both the generation of secret keys from biometric data and the binding of secret keys to biometric data are investigated. These secret keys can be used to regulate access to sensitive data, services, and environments. In a biometric secrecy system a secret key is generated or chosen

  13. Biometric security from an information-theoretical perspective

    NARCIS (Netherlands)

    Ignatenko, T.; Willems, F.M.J.

    2012-01-01

    In this review, biometric systems are studied from an information theoretical point of view. In the first part biometric authentication systems are studied. The objective of these systems is, observing correlated enrollment and authentication biometric sequences, to generate or convey as large as

  14. Correlation of iris biometrics and DNA

    DEFF Research Database (Denmark)

    Harder, Stine; Clemmensen, Line Katrine Harder; Dahl, Anders Bjorholm

    2013-01-01

    The presented work concerns prediction of complex human phenotypes from genotypes. We were interested in correlating iris color and texture with DNA. Our data consist of 212 eye images along with DNA: 32 single-nucleotide polymorphisms (SNPs). We used two types of biometrics to describe the eye...... images: One for iris color and one for iris texture. Both biometrics were high dimensional and a sparse principle component analysis (SPCA) reduced the dimensions and resulted in a representation of data with good interpretability. The correlations between the sparse principal components (SPCs......) and the 32 SNPs were found using a canonical correlation analysis (CCA). The result was a single significant canonical correlation (CC) for both biometrics. Each CC comprised two correlated canonical variables, consisting of a linear combination of SPCs and a linear combination of SNPs, respectively...

  15. Animal biometrics: quantifying and detecting phenotypic appearance.

    Science.gov (United States)

    Kühl, Hjalmar S; Burghardt, Tilo

    2013-07-01

    Animal biometrics is an emerging field that develops quantified approaches for representing and detecting the phenotypic appearance of species, individuals, behaviors, and morphological traits. It operates at the intersection between pattern recognition, ecology, and information sciences, producing computerized systems for phenotypic measurement and interpretation. Animal biometrics can benefit a wide range of disciplines, including biogeography, population ecology, and behavioral research. Currently, real-world applications are gaining momentum, augmenting the quantity and quality of ecological data collection and processing. However, to advance animal biometrics will require integration of methodologies among the scientific disciplines involved. Such efforts will be worthwhile because the great potential of this approach rests with the formal abstraction of phenomics, to create tractable interfaces between different organizational levels of life. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Enhancing Privacy for Biometric Identification Cards

    Directory of Open Access Journals (Sweden)

    2009-01-01

    Full Text Available Most developed countries have started the implementation of biometric electronic identification cards, especially passports. The European Union and the United States of America struggle to introduce and standardize these electronic documents. Due to the personal nature of the biometric elements used for the generation of these cards, privacy issues were raised on both sides of the Atlantic Ocean, leading to civilian protests and concerns. The lack of transparency from the public authorities responsible with the implementation of such identification systems, and the poor technological approaches chosen by these authorities, are the main reasons for the negative popularity of the new identification methods. The following article shows an approach that provides all the benefits of modern technological advances in the fields of biometrics and cryptography, without sacrificing the privacy of those that will be the beneficiaries of the new system

  17. Analyzing personalized policies for online biometric verification.

    Science.gov (United States)

    Sadhwani, Apaar; Yang, Yan; Wein, Lawrence M

    2014-01-01

    Motivated by India's nationwide biometric program for social inclusion, we analyze verification (i.e., one-to-one matching) in the case where we possess similarity scores for 10 fingerprints and two irises between a resident's biometric images at enrollment and his biometric images during his first verification. At subsequent verifications, we allow individualized strategies based on these 12 scores: we acquire a subset of the 12 images, get new scores for this subset that quantify the similarity to the corresponding enrollment images, and use the likelihood ratio (i.e., the likelihood of observing these scores if the resident is genuine divided by the corresponding likelihood if the resident is an imposter) to decide whether a resident is genuine or an imposter. We also consider two-stage policies, where additional images are acquired in a second stage if the first-stage results are inconclusive. Using performance data from India's program, we develop a new probabilistic model for the joint distribution of the 12 similarity scores and find near-optimal individualized strategies that minimize the false reject rate (FRR) subject to constraints on the false accept rate (FAR) and mean verification delay for each resident. Our individualized policies achieve the same FRR as a policy that acquires (and optimally fuses) 12 biometrics for each resident, which represents a five (four, respectively) log reduction in FRR relative to fingerprint (iris, respectively) policies previously proposed for India's biometric program. The mean delay is [Formula: see text] sec for our proposed policy, compared to 30 sec for a policy that acquires one fingerprint and 107 sec for a policy that acquires all 12 biometrics. This policy acquires iris scans from 32-41% of residents (depending on the FAR) and acquires an average of 1.3 fingerprints per resident.

  18. Improvement of security techniques and protection of biometric data in biometric systems: Presentation of International Standard ISO 24745

    OpenAIRE

    Milinković, Milorad

    2017-01-01

    This paper presents the International Standard ISO 24745 as a potential security tool for biometric information protection, more precisely as a tool for privacy protection in biometric systems. This is one of the latest internationally accepted standards that address the security issues of biometric systems.

  19. Privacy Enhancements for Inexact Biometric Templates

    Science.gov (United States)

    Ratha, Nalini; Chikkerur, Sharat; Connell, Jonathan; Bolle, Ruud

    Traditional authentication schemes utilize tokens or depend on some secret knowledge possessed by the user for verifying his or her identity. Although these techniques are widely used, they have several limitations. Both tokenand knowledge-based approaches cannot differentiate between an authorized user and an impersonator having access to the tokens or passwords. Biometrics-based authentication schemes overcome these limitations while offering usability advantages in the area of password management. However, despite its obvious advantages, the use of biometrics raises several security and privacy concerns.

  20. Mathematical and information maintenance of biometric systems

    Science.gov (United States)

    Boriev, Z.; Sokolov, S.; Nyrkov, A.; Nekrasova, A.

    2016-04-01

    This article describes the different mathematical methods for processing biometric data. A brief overview of methods for personality recognition by means of a signature is conducted. Mathematical solutions of a dynamic authentication method are considered. Recommendations on use of certain mathematical methods, depending on specific tasks, are provided. Based on the conducted analysis of software and the choice made in favor of the wavelet analysis, a brief basis for its use in the course of software development for biometric personal identification is given for the purpose of its practical application.

  1. Multimodality imaging features of hereditary multiple exostoses

    OpenAIRE

    Kok, H K; Fitzgerald, L; Campbell, N; Lyburn, I D; Munk, P L; Buckley, O; Torreggiani, W C

    2013-01-01

    Hereditary multiple exostoses (HME) or diaphyseal aclasis is an inherited disorder characterised by the formation of multiple osteochondromas, which are cartilage-capped osseous outgrowths, and the development of associated osseous deformities. Individuals with HME may be asymptomatic or develop clinical symptoms, which prompt imaging studies. Different modalities ranging from plain radiographs to cross-sectional and nuclear medicine imaging studies can be helpful in the diagnosis and detecti...

  2. Unveiling the Biometric Potential of Finger-Based ECG Signals

    Science.gov (United States)

    Lourenço, André; Silva, Hugo; Fred, Ana

    2011-01-01

    The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235

  3. Ultrasound of the fingers for human identification using biometrics.

    Science.gov (United States)

    Narayanasamy, Ganesh; Fowlkes, J Brian; Kripfgans, Oliver D; Jacobson, Jon A; De Maeseneer, Michel; Schmitt, Rainer M; Carson, Paul L

    2008-03-01

    It was hypothesized that the use of internal finger structure as imaged using commercially available ultrasound (US) scanners could act as a supplement to standard methods of biometric identification, as well as a means of assessing physiological and cardiovascular status. Anatomical structures in the finger including bone contour, tendon and features along the interphalangeal joint were investigated as potential biometric identifiers. Thirty-six pairs of three-dimensional (3D) gray-scale images of second to fourth finger (index, middle and ring) data taken from 20 individuals were spatially registered using MIAMI-Fuse software developed at our institution and also visually matched by four readers. The image-based registration met the criteria for matching successfully in 14 out of 15 image pairs on the same individual and did not meet criteria for matching in any of the 12 image pairs from different subjects, providing a sensitivity and specificity of 0.93 and 1.00, respectively. Visual matching of all image pairs by four readers yielded 96% successful match. Power Doppler imaging was performed to calculate the change in color pixel density due to physical exercise as a surrogate of stress level and to provide basic physiological information. (E-mail: gnarayan@umich.edu).

  4. Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

    Directory of Open Access Journals (Sweden)

    Tong Liu

    2017-12-01

    Full Text Available This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF links for path-dependent walker classification. The fluctuated received signal strength (RSS sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ and hidden Markov models (HMMs are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS and non-line-of-sight (NLOS scenarios are conducted to validate the proposed method.

  5. Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links.

    Science.gov (United States)

    Liu, Tong; Liang, Zhuo-Qian

    2017-12-05

    This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method.

  6. Unveiling the biometric potential of finger-based ECG signals.

    Science.gov (United States)

    Lourenço, André; Silva, Hugo; Fred, Ana

    2011-01-01

    The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

  7. Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

    Science.gov (United States)

    Liang, Zhuo-qian

    2017-01-01

    This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method. PMID:29206188

  8. BIOMETRIC IDENTITY VERIFICATION IN HEALTH SERVICES: A BIOMETRIC SURVEILLANCE PRACTICE IN TURKEY

    OpenAIRE

    İlker ŞİRİN

    2014-01-01

    Determination or verification of identity with biometric methods has a widespread use especially at borders for security reasons. Social Security Institution transferred the biometric identity verification practice to health sercives that are provided by private and university hospitals. The risks of the new system considering the privacy of personal data are under debate. Although there are announcements or manuals of Social Security Institution regarding the implementation...

  9. A Systems Approach to Biometrics in the Military Domain.

    Science.gov (United States)

    Wilson, Lauren; Gahan, Michelle; Lennard, Chris; Robertson, James

    2018-02-21

    Forensic biometrics is the application of forensic science principles to physical and behavioral characteristics. Forensic biometrics is a secondary sub-system in the forensic science "system of systems," which describes forensic science as a sub-system in the larger criminal justice, law enforcement, intelligence, and military system. The purpose of this paper is to discuss biometrics in the military domain and integration into the wider forensic science system of systems. The holistic system thinking methodology was applied to the U.S. biometric system to map it to the system of systems framework. The U.S. biometric system is used as a case study to help guide other countries to develop military biometric systems that are integrated and interoperable at the whole-of-government level. The aim is to provide the system of systems framework for agencies to consider for proactive design of biometric systems. © 2018 American Academy of Forensic Sciences.

  10. Percorsi linguistici e semiotici: Critical Multimodal Analysis of Digital Discourse

    Directory of Open Access Journals (Sweden)

    edited by Ilaria Moschini

    2014-12-01

    Full Text Available The language section of LEA - edited by Ilaria Moschini - is dedicated to the Critical Multimodal Analysis of Digital Discourse, an approach that encompasses the linguistic and semiotic detailed investigation of texts within a socio-cultural perspective. It features an interview with Professor Theo van Leeuwen by Ilaria Moschini and four essays: “Retwitting, reposting, repinning; reshaping identities online: Towards a social semiotic multimodal analysis of digital remediation” by Elisabetta Adami; “Multimodal aspects of corporate social responsibility communication” by Carmen Daniela Maier; “Pervasive Technologies and the Paradoxes of Multimodal Digital Communication” by Sandra Petroni and “Can the powerless speak? Linguistic and multimodal corporate media manipulation in digital environments: the case of Malala Yousafzai” by Maria Grazia Sindoni. 

  11. Trace Attack against Biometric Mobile Applications

    Directory of Open Access Journals (Sweden)

    Sanaa Ghouzali

    2016-01-01

    Full Text Available With the exponential increase in the dependence on mobile devices in everyday life, there is a growing concern related to privacy and security issues in the Gulf countries; therefore, it is imperative that security threats should be analyzed in detail. Mobile devices store enormous amounts of personal and financial information, unfortunately without any security. In order to secure mobile devices against different threats, biometrics has been applied and shown to be effective. However, biometric mobile applications are also vulnerable to several types of attacks that can decrease their security. Biometric information itself is considered sensitive data; for example, fingerprints can leave traces in touched objects and facial images can be captured everywhere or accessed by the attacker if the facial image is stored in the mobile device (lost or stolen. Hence, an attacker can easily forge the identity of a legitimate user and access data on a device. In this paper, the effects of a trace attack on the sensitivity of biometric mobile applications are investigated in terms of security and user privacy. Experimental results carried out on facial and fingerprint mobile authentication applications using different databases have shown that these mobile applications are vulnerable to the proposed attack, which poses a serious threat to the overall system security and user privacy.

  12. Capillary-Patterns for Biometric Authentication

    NARCIS (Netherlands)

    Paloma Benedicto, J.; Bruekers, A.A.M.; Presura, C.N.; Garcia Molina, G.

    2007-01-01

    In this report, we present a method using the capillary structuresunder the "distal interphalangeal joint" (DIP joint), which is located between the second and third (distal) phalanges of the finger, for achieving secure biometric authentication. Images of the DIPjoint are acquired using a

  13. Quantum Biometrics with Retinal Photon Counting

    Science.gov (United States)

    Loulakis, M.; Blatsios, G.; Vrettou, C. S.; Kominis, I. K.

    2017-10-01

    It is known that the eye's scotopic photodetectors, rhodopsin molecules, and their associated phototransduction mechanism leading to light perception, are efficient single-photon counters. We here use the photon-counting principles of human rod vision to propose a secure quantum biometric identification based on the quantum-statistical properties of retinal photon detection. The photon path along the human eye until its detection by rod cells is modeled as a filter having a specific transmission coefficient. Precisely determining its value from the photodetection statistics registered by the conscious observer is a quantum parameter estimation problem that leads to a quantum secure identification method. The probabilities for false-positive and false-negative identification of this biometric technique can readily approach 10-10 and 10-4, respectively. The security of the biometric method can be further quantified by the physics of quantum measurements. An impostor must be able to perform quantum thermometry and quantum magnetometry with energy resolution better than 10-9ℏ , in order to foil the device by noninvasively monitoring the biometric activity of a user.

  14. Towards Biometric Assessment of Audience Affect

    DEFF Research Database (Denmark)

    Lyng Wieland, Jakob; Larsen, Lars Bo; Laursen, Jeanette Kølbæk

    2016-01-01

    This paper investigates how reliable affective responses can be obtained using objective biometric measures for media audience research. We use Galvanic Skin Response (GSR) to detect sixteen respondents’ arousal levels and as an objective measure to show how self- reporting disrupts the experience...

  15. Analysis of eigenvalue correction applied to biometrics

    NARCIS (Netherlands)

    Hendrikse, A.J.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan; Bazen, A.M.

    Eigenvalue estimation plays an important role in biometrics. However, if the number of samples is limited, estimates are significantly biased. In this article we analyse the influence of this bias on the error rates of PCA/LDA based verification systems, using both synthetic data with realistic

  16. Biometric authentication for a mobile personal device

    NARCIS (Netherlands)

    Tao, Q.; Veldhuis, Raymond N.J.

    2006-01-01

    Secure access is prerequisite for a mobile personal device (MPD) in a personal network (PN). An authentication method using biometrics, specifically face, is proposed in this paper. A fast face detection and registration method based on a Viola-Jones detector is implemented, and a

  17. Biometric Authentication System on Mobile Personal Devices

    NARCIS (Netherlands)

    Tao, Q.; Veldhuis, Raymond N.J.

    We propose a secure, robust, and low-cost biometric authentication system on the mobile personal device for the personal network. The system consists of the following five key modules: 1) face detection; 2) face registration; 3) illumination normalization; 4) face verification; and 5) information

  18. Extracting forensic evidence from biometric devices

    Science.gov (United States)

    Geradts, Zeno J.; Ruifrok, Arnout C.

    2003-08-01

    Over the past few years, both large multinationals and governments have begun to contribute to even larger projects on biometric devices. Terrorist attacks in America and in other countries have highlighted the need for better identification systems for people as well as improved systems for controlling access to buildings. Another reason for investment in Research and Development in Biometric Devices, is the massive growth in internet-based systems -- whether for e-commerce, e-government or internal processes within organizations. The interface between the system and the user is routinely abused, as people have to remember many complex passwords and handle tokens of various types. In this paper an overview is given of the information that is important to know before an examination of such is systems can be done in a forensic proper way. In forensic evidence with biometric devices the forensic examiner should consider the possibilities of tampering with the biometric systems or the possibilities of unauthorized access before drawing conclusions.

  19. Zero leakage quantization scheme for biometric verification

    NARCIS (Netherlands)

    Groot, de J.A.; Linnartz, J.P.M.G.

    2011-01-01

    Biometrics gain increasing interest as a solution for many security issues, but privacy risks exist in case we do not protect the stored templates well. This paper presents a new verification scheme, which protects the secrets of the enrolled users. We will show that zero leakage is achieved if

  20. Multimodal freight investment criteria.

    Science.gov (United States)

    2010-07-01

    Literature was reviewed on multi-modal investment criteria for freight projects, examining measures and techniques for quantifying project benefits and costs, as well as ways to describe the economic importance of freight transportation. : A limited ...

  1. Voice Biometrics over the Internet in the Framework of COST Action 275

    Directory of Open Access Journals (Sweden)

    Evans Nicholas WD

    2004-01-01

    Full Text Available The emerging field of biometric authentication over the Internet requires both robust person authentication and secure computer network protocols. This paper presents investigations of vocal biometric person authentication over the Internet, both at the protocol and authentication robustness levels. As part of this study, an appropriate client-server architecture for biometrics on the Internet is proposed and implemented. It is shown that the transmission of raw biometric data in this application is likely to result in unacceptably long delays in the process. On the other hand, by using data models (or features, the transmission time can be reduced to an acceptable level. The use of encryption/decryption for enhancing the data security in the proposed client-server link and its effects on the transmission time are also examined. Furthermore, the scope of the investigations includes an analysis of the effects of packet loss and speech coding on speaker verification performance. It is experimentally demonstrated that whilst the adverse effects of packet loss can be negligible, the encoding of speech, particularly at a low bit rate, can reduce the verification accuracy considerably. The paper details the experimental investigations conducted and presents an analysis of the results.

  2. Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition.

    Science.gov (United States)

    Galbally, Javier; Marcel, Sébastien; Fierrez, Julian

    2014-02-01

    To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of biometric recognition frameworks, by adding liveness assessment in a fast, user-friendly, and non-intrusive manner, through the use of image quality assessment. The proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using 25 general image quality features extracted from one image (i.e., the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results, obtained on publicly available data sets of fingerprint, iris, and 2D face, show that the proposed method is highly competitive compared with other state-of-the-art approaches and that the analysis of the general image quality of real biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.

  3. Learning multimodal dictionaries.

    Science.gov (United States)

    Monaci, Gianluca; Jost, Philippe; Vandergheynst, Pierre; Mailhé, Boris; Lesage, Sylvain; Gribonval, Rémi

    2007-09-01

    Real-world phenomena involve complex interactions between multiple signal modalities. As a consequence, humans are used to integrate at each instant perceptions from all their senses in order to enrich their understanding of the surrounding world. This paradigm can be also extremely useful in many signal processing and computer vision problems involving mutually related signals. The simultaneous processing of multimodal data can, in fact, reveal information that is otherwise hidden when considering the signals independently. However, in natural multimodal signals, the statistical dependencies between modalities are in general not obvious. Learning fundamental multimodal patterns could offer deep insight into the structure of such signals. In this paper, we present a novel model of multimodal signals based on their sparse decomposition over a dictionary of multimodal structures. An algorithm for iteratively learning multimodal generating functions that can be shifted at all positions in the signal is proposed, as well. The learning is defined in such a way that it can be accomplished by iteratively solving a generalized eigenvector problem, which makes the algorithm fast, flexible, and free of user-defined parameters. The proposed algorithm is applied to audiovisual sequences and it is able to discover underlying structures in the data. The detection of such audio-video patterns in audiovisual clips allows to effectively localize the sound source on the video in presence of substantial acoustic and visual distractors, outperforming state-of-the-art audiovisual localization algorithms.

  4. Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

    Science.gov (United States)

    Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

    2017-07-01

    Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

  5. Multimodality Registration without a Dedicated Multimodality Scanner

    Directory of Open Access Journals (Sweden)

    Bradley J. Beattie

    2007-03-01

    Full Text Available Multimodality scanners that allow the acquisition of both functional and structural image sets on a single system have recently become available for animal research use. Although the resultant registered functional/structural image sets can greatly enhance the interpretability of the functional data, the cost of multimodality systems can be prohibitive, and they are often limited to two modalities, which generally do not include magnetic resonance imaging. Using a thin plastic wrap to immobilize and fix a mouse or other small animal atop a removable bed, we are able to calculate registrations between all combinations of four different small animal imaging scanners (positron emission tomography, single-photon emission computed tomography, magnetic resonance, and computed tomography [CT] at our disposal, effectively equivalent to a quadruple-modality scanner. A comparison of serially acquired CT images, with intervening acquisitions on other scanners, demonstrates the ability of the proposed procedures to maintain the rigidity of an anesthetized mouse during transport between scanners. Movement of the bony structures of the mouse was estimated to be 0.62 mm. Soft tissue movement was predominantly the result of the filling (or emptying of the urinary bladder and thus largely constrained to this region. Phantom studies estimate the registration errors for all registration types to be less than 0.5 mm. Functional images using tracers targeted to known structures verify the accuracy of the functional to structural registrations. The procedures are easy to perform and produce robust and accurate results that rival those of dedicated multimodality scanners, but with more flexible registration combinations and while avoiding the expense and redundancy of multimodality systems.

  6. BIOMETRIC SECURITY: ALTERNATIF PENGENDALIAN DALAM SISTEM INFORMASI AKUNTANSI TERKOMPUTERISASI

    Directory of Open Access Journals (Sweden)

    Josua Tarigan

    2004-01-01

    Full Text Available As organization search more secure authentication method for user access, biometric security technology is gaining more and more attention. The implementation of biometric security technology in accounting information systems was physical access, virtual access, e-commerce applications and covert suveillance. There are three phase when an organization implementation biometric technology: strategic planning and budgeting, developing a system reliability plan and documentation. The challenges will face when develop biometric technology as control in accounting information system are standardization, hybrid technology uses, life cycle management. Abstract in Bahasa Indonesia : Adanya keinginan setiap organisasi untuk mencari metode pengamanan authentication yang lebih untuk akses user, dijawab dengan adanya teknologi biometric security yang mendapat perhatian yang cukup besar bagi organisasi. Implementasi teknologi biometric security cukup luas dalam sistem informasi akuntansi yaitu sebagai pengendalian pada physical access, virtual access, e-commerce applications dan covert surveillance. Dalam mengimplementasikan teknologi biometric, ada tiga tahapan yang harus dilakukan organisasi, yakni strategic planning and budgeting, developing a system reliability plan dan documentation. Tantangan yang akan dihadapi dalam mengembangkan teknologi biometric sebagai pengendalian dalam sistem informasi akuntansi yakni standarisasi, aplikasi teknologi hybrid dan manajemen siklus hidup pada biometric security. Kata kunci: authentication, akses user dan biometric security.

  7. Towards an intelligent framework for multimodal affective data analysis.

    Science.gov (United States)

    Poria, Soujanya; Cambria, Erik; Hussain, Amir; Huang, Guang-Bin

    2015-03-01

    An increasingly large amount of multimodal content is posted on social media websites such as YouTube and Facebook everyday. In order to cope with the growth of such so much multimodal data, there is an urgent need to develop an intelligent multi-modal analysis framework that can effectively extract information from multiple modalities. In this paper, we propose a novel multimodal information extraction agent, which infers and aggregates the semantic and affective information associated with user-generated multimodal data in contexts such as e-learning, e-health, automatic video content tagging and human-computer interaction. In particular, the developed intelligent agent adopts an ensemble feature extraction approach by exploiting the joint use of tri-modal (text, audio and video) features to enhance the multimodal information extraction process. In preliminary experiments using the eNTERFACE dataset, our proposed multi-modal system is shown to achieve an accuracy of 87.95%, outperforming the best state-of-the-art system by more than 10%, or in relative terms, a 56% reduction in error rate. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Context-Aware Multimodal FIDO Authenticator for Sustainable IT Services

    Directory of Open Access Journals (Sweden)

    Seung-Hyun Kim

    2018-05-01

    Full Text Available Existing sustainable IT services have several problems related to user authentication such as the inefficiency of managing the system security, low security, and low usability. In this paper, we propose a Fast IDentity Online (FIDO authenticator that performs continuous authentication with implicit authentication based on user context and multimodal authentication. The proposed FIDO authenticator, a context-aware multimodal FIDO authentication (CAMFA method, combines information such as the user context, state of the mobile device, and user biometrics, then applies implicit and explicit authentication methods to meet the level of authentication required by the service provider. This reduces the user’s explicit authentication burden and continually authenticates users at risk during the session. Moreover, it is able to respond to attacks such as the theft of the authentication method or session hijacking. To study the effectiveness of CAMFA, we ran a user study by collecting data from 22 participants over 42 days of activity on a practical Android platform. The result of the user study demonstrates that the number of explicit authentication requests could be reduced by half. Based on the results of this study, an advanced user authentication that provides multimodal and continuous authentication could be applied to sustainable IT services.

  9. Multimodal Resources in Transnational Adoption

    DEFF Research Database (Denmark)

    Raudaskoski, Pirkko Liisa

    The paper discusses an empirical analysis which highlights the multimodal nature of identity construction. A documentary on transnational adoption provides real life incidents as research material. The incidents involve (or from them emerge) various kinds of multimodal resources and participants...

  10. On Hunting Animals of the Biometric Menagerie for Online Signature.

    Directory of Open Access Journals (Sweden)

    Nesma Houmani

    Full Text Available Individuals behave differently regarding to biometric authentication systems. This fact was formalized in the literature by the concept of Biometric Menagerie, defining and labeling user groups with animal names in order to reflect their characteristics with respect to biometric systems. This concept was illustrated for face, fingerprint, iris, and speech modalities. The present study extends the Biometric Menagerie to online signatures, by proposing a novel methodology that ties specific quality measures for signatures to categories of the Biometric Menagerie. Such measures are combined for retrieving automatically writer categories of the extended version of the Biometric Menagerie. Performance analysis with different types of classifiers shows the pertinence of our approach on the well-known MCYT-100 database.

  11. On Hunting Animals of the Biometric Menagerie for Online Signature.

    Science.gov (United States)

    Houmani, Nesma; Garcia-Salicetti, Sonia

    2016-01-01

    Individuals behave differently regarding to biometric authentication systems. This fact was formalized in the literature by the concept of Biometric Menagerie, defining and labeling user groups with animal names in order to reflect their characteristics with respect to biometric systems. This concept was illustrated for face, fingerprint, iris, and speech modalities. The present study extends the Biometric Menagerie to online signatures, by proposing a novel methodology that ties specific quality measures for signatures to categories of the Biometric Menagerie. Such measures are combined for retrieving automatically writer categories of the extended version of the Biometric Menagerie. Performance analysis with different types of classifiers shows the pertinence of our approach on the well-known MCYT-100 database.

  12. On enabling secure applications through off-line biometric identification

    Energy Technology Data Exchange (ETDEWEB)

    Davida, G.I. [Univ. of Wisconsin, Milwaukee, WI (United States); Frankel, Y. [CertCo LLC, New York, NY (United States); Matt, B.J. [Sandia National Labs., Albuquerque, NM (United States)

    1998-04-01

    In developing secure applications and systems, the designers often must incorporate secure user identification in the design specification. In this paper, the authors study secure off line authenticated user identification schemes based on a biometric system that can measure a user`s biometric accurately (up to some Hamming distance). The schemes presented here enhance identification and authorization in secure applications by binding a biometric template with authorization information on a token such as a magnetic strip. Also developed here are schemes specifically designed to minimize the compromise of a user`s private biometrics data, encapsulated in the authorization information, without requiring secure hardware tokens. In this paper the authors furthermore study the feasibility of biometrics performing as an enabling technology for secure system and application design. The authors investigate a new technology which allows a user`s biometrics to facilitate cryptographic mechanisms.

  13. On enabling secure applications through off-line biometric identification

    International Nuclear Information System (INIS)

    Davida, G.I.; Frankel, Y.; Matt, B.J.

    1998-04-01

    In developing secure applications and systems, the designers often must incorporate secure user identification in the design specification. In this paper, the authors study secure off line authenticated user identification schemes based on a biometric system that can measure a user's biometric accurately (up to some Hamming distance). The schemes presented here enhance identification and authorization in secure applications by binding a biometric template with authorization information on a token such as a magnetic strip. Also developed here are schemes specifically designed to minimize the compromise of a user's private biometrics data, encapsulated in the authorization information, without requiring secure hardware tokens. In this paper the authors furthermore study the feasibility of biometrics performing as an enabling technology for secure system and application design. The authors investigate a new technology which allows a user's biometrics to facilitate cryptographic mechanisms

  14. Remote Biometrics for Robust Persistent Authentication

    DEFF Research Database (Denmark)

    Ingwar, Mads Ingerslew; Jensen, Christian D.

    2014-01-01

    This paper examines the problem of providing a robust non-invasive authentication service for mobile users in a smart environment. We base our work on the persistent authentication model (PAISE), which relies on available sensors to track principals from the location where they authenticate, e.......g., through a smart card based access control system, to the location where the authentication is required by a location-based service. The PAISE model is extended with remote biometrics to prevent the decay of authentication confidence when authenticated users encounter and interact with other users...... in the environment. The result is a calm approach to authentication, where mobile users are transparently authenticated towards the system, which allows the provision of location-based services. The output of the remote biometrics are fused using error-rate-based fusion to solve a common problem that occurs in score...

  15. Carbon Nanotube Embedded Nanostructure for Biometrics.

    Science.gov (United States)

    Park, Juhyuk; Youn, Jae Ryoun; Song, Young Seok

    2017-12-27

    Low electric energy loss is a very important problem to minimize the decay of transferred energy intensity due to impedance mismatch. This issue has been dealt with by adding an impedance matching layer at the interface between two media. A strategy was proposed to improve the charge transfer from the human body to a biometric device by using an impedance matching nanostructure. Nanocomposite pattern arrays were fabricated with shape memory polymer and carbon nanotubes. The shape recovery ability of the nanopatterns enhanced durability and sustainability of the structure. It was found that the composite nanopatterns improved the current transfer by two times compared with the nonpatterned composite sample. The underlying mechanism of the enhanced charge transport was understood by carrying out a numerical simulation. We anticipate that this study can provide a new pathway for developing advanced biometric devices with high sensitivity to biological information.

  16. Evaluation methodologies for security testing biometric systems beyond technological evaluation

    OpenAIRE

    Fernández Saavedra, María Belén

    2013-01-01

    The main objective of this PhD Thesis is the specification of formal evaluation methodologies for testing the security level achieved by biometric systems when these are working under specific contour conditions. This analysis is conducted through the calculation of the basic technical biometric system performance and its possible variations. To that end, the next two relevant contributions have been developed. The first contribution is the definition of two independent biometric performance ...

  17. Towards the Security Evaluation of Biometric Authentication Systems

    OpenAIRE

    El-Abed , Mohamad; Giot , Romain; Hemery , Baptiste; Rosenberger , Christophe; Schwartzmann , Jean-Jacques

    2011-01-01

    International audience; Despite the obvious advantages of biometric authentication systems over traditional security ones (based on tokens or passwords), they are vulnerable to attacks which may considerably decrease their security. In order to contribute in resolving such problematic, we propose a modality-independent evaluation methodology for the security evaluation of biometric systems. It is based on the use of a database of common threats and vulnerabilities of biometric systems, and th...

  18. Biometric Authentication System using Non-Linear Chaos

    OpenAIRE

    Dr.N.Krishnan; A.Senthil Arumugam,

    2010-01-01

    A major concern nowadays for any Biometric Credential Management System is its potential vulnerability to protect its information sources; i.e. protecting a genuine user’s template from both internal and external threats. These days’ biometric authentication systems face various risks. One of the most serious threats is the ulnerability of the template's database. An attacker with access to a reference template could try to impersonate a legitimate user by reconstructing the biometric sample...

  19. Behavioural Biometrics for Multi-factor Authentication in Biomedicine

    Czech Academy of Sciences Publication Activity Database

    Schlenker, Anna; Šárek, M.

    2012-01-01

    Roč. 8, č. 5 (2012), s. 19-24 ISSN 1801-5603 Grant - others:GA MŠk(CZ) LM2010005; GA UK(CZ) SVV-2012-264513 Institutional support: RVO:67985807 Keywords : biometric s * anatomical-physiological biometric s * behavioural biometric s * multi-factor authentication * keystroke dynamics * mouse dynamics Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/img/ejbi/2012/5/Schlenker_en.pdf

  20. Biometric Security: Alternatif Pengendalian Dalam Sistem Informasi Akuntansi Terkomputerisasi

    OpenAIRE

    Tarigan, Josua

    2004-01-01

    As organization search more secure authentication method for user access, biometric security technology is gaining more and more attention. The implementation of biometric security technology in accounting information systems was physical access, virtual access, e-commerce applications and covert suveillance. There are three phase when an organization implementation biometric technology: strategic planning and budgeting, developing a system reliability plan and documentation. The challenges w...

  1. BIOMETRIC SECURITY: ALTERNATIF PENGENDALIAN DALAM SISTEM INFORMASI AKUNTANSI TERKOMPUTERISASI

    OpenAIRE

    Josua Tarigan

    2004-01-01

    As organization search more secure authentication method for user access, biometric security technology is gaining more and more attention. The implementation of biometric security technology in accounting information systems was physical access, virtual access, e-commerce applications and covert suveillance. There are three phase when an organization implementation biometric technology: strategic planning and budgeting, developing a system reliability plan and documentation. The challenges w...

  2. Prospects of Biometrics at-a-Distance

    Science.gov (United States)

    2015-09-01

    face or fingerprint. For instance, light levels affect the ability of the sensor to collect accurate imagery (Pato & Millet , 2010). When conducting...accurate data on a subject given environmental or hardware restraints (Pato & Millet , 2010). These issues degrade biometric system capabilities when...where the arch pattern looks more like a hill with ridges entering from one side, moving across the finger while rising, then falling and exiting the

  3. A biometric approach to laboratory rodent identification.

    Science.gov (United States)

    Cameron, Jens; Jacobson, Christina; Nilsson, Kenneth; Rögnvaldsson, Thorsteinn

    2007-03-01

    Individual identification of laboratory rodents typically involves invasive methods, such as tattoos, ear clips, and implanted transponders. Beyond the ethical dilemmas they may present, these methods may cause pain or distress that confounds research results. The authors describe a prototype device for biometric identification of laboratory rodents that would allow researchers to identify rodents without the complications of other methods. The device, which uses the rodent's ear blood vessel pattern as the identifier, is fast, automatic, noninvasive, and painless.

  4. Device for biometric verification of maternity

    OpenAIRE

    Lalović Komlen; Milosavljević Milan; Tot Ivan; Maček Nemanja

    2015-01-01

    Biometry is the scientific discipline and technology that measures and analyzes physiological or behavioral characteristics of people and is widely deployed in modern society security systems. Device for biometric identification of maternity is a dual fingerprint scanner that acquires fingerprint templates of the mother and the child at the very moment of birth, generates unique ID reference, and further guarantees mother-child relationship with that refere...

  5. Biometric Methods for Application in Biomedicine

    Czech Academy of Sciences Publication Activity Database

    Schlenker, Anna; Šárek, Milan

    2011-01-01

    Roč. 7, č. 1 (2011), s. 37-43 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : biometrics * data security * EHR ( electronic health record ) * fingerprints * hand geometry * face recognition * iris recognition * retinal scanning * keystroke dynamics * multi-factor authentification Subject RIV: IN - Informatics, Computer Science http://www.ejbi.eu/images/2011-1/Schlenker_en.pdf

  6. Iris analysis for biometric recognition systems

    CERN Document Server

    Bodade, Rajesh M

    2014-01-01

    The book presents three most significant areas in Biometrics and Pattern Recognition. A step-by-step approach for design and implementation of Dual Tree Complex Wavelet Transform (DTCWT) plus Rotated Complex Wavelet Filters (RCWF) is discussed in detail. In addition to the above, the book provides detailed analysis of iris images and two methods of iris segmentation. It also discusses simplified study of some subspace-based methods and distance measures for iris recognition backed by empirical studies and statistical success verifications.

  7. Heart Electrical Actions as Biometric Indicia

    Science.gov (United States)

    Schipper, John F. (Inventor); Dusan, Sorin V. (Inventor); Jorgensen, Charles C. (Inventor); Belousof, Eugene (Inventor)

    2013-01-01

    A method and associated system for use of statistical parameters based on peak amplitudes and/or time interval lengths and/or depolarization-repolarization vector angles and/or depolarization-repolarization vector lengths for PQRST electrical signals associated with heart waves, to identify a person. The statistical parameters, estimated to be at least 192, serve as biometric indicia, to authenticate, or to decline to authenticate, an asserted identity of a candidate person.

  8. Multimodal sequence learning.

    Science.gov (United States)

    Kemény, Ferenc; Meier, Beat

    2016-02-01

    While sequence learning research models complex phenomena, previous studies have mostly focused on unimodal sequences. The goal of the current experiment is to put implicit sequence learning into a multimodal context: to test whether it can operate across different modalities. We used the Task Sequence Learning paradigm to test whether sequence learning varies across modalities, and whether participants are able to learn multimodal sequences. Our results show that implicit sequence learning is very similar regardless of the source modality. However, the presence of correlated task and response sequences was required for learning to take place. The experiment provides new evidence for implicit sequence learning of abstract conceptual representations. In general, the results suggest that correlated sequences are necessary for implicit sequence learning to occur. Moreover, they show that elements from different modalities can be automatically integrated into one unitary multimodal sequence. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Robust Multimodal Dictionary Learning

    Science.gov (United States)

    Cao, Tian; Jojic, Vladimir; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

    2014-01-01

    We propose a robust multimodal dictionary learning method for multimodal images. Joint dictionary learning for both modalities may be impaired by lack of correspondence between image modalities in training data, for example due to areas of low quality in one of the modalities. Dictionaries learned with such non-corresponding data will induce uncertainty about image representation. In this paper, we propose a probabilistic model that accounts for image areas that are poorly corresponding between the image modalities. We cast the problem of learning a dictionary in presence of problematic image patches as a likelihood maximization problem and solve it with a variant of the EM algorithm. Our algorithm iterates identification of poorly corresponding patches and re-finements of the dictionary. We tested our method on synthetic and real data. We show improvements in image prediction quality and alignment accuracy when using the method for multimodal image registration. PMID:24505674

  10. Critical Analysis of Multimodal Discourse

    DEFF Research Database (Denmark)

    van Leeuwen, Theo

    2013-01-01

    This is an encyclopaedia article which defines the fields of critical discourse analysis and multimodality studies, argues that within critical discourse analysis more attention should be paid to multimodality, and within multimodality to critical analysis, and ends reviewing a few examples of re...

  11. Robust and Secure Watermarking Using Sparse Information of Watermark for Biometric Data Protection

    OpenAIRE

    Rohit M Thanki; Ved Vyas Dwivedi; Komal Borisagar

    2016-01-01

    Biometric based human authentication system is used for security purpose in many organizations in the present world. This biometric authentication system has several vulnerable points. Two of vulnerable points are protection of biometric templates at system database and protection of biometric templates at communication channel between two modules of biometric authentication systems. In this paper proposed a robust watermarking scheme using the sparse information of watermark biometric to sec...

  12. Biometric technology authentication, biocryptography, and cloud-based architecture

    CERN Document Server

    Das, Ravi

    2014-01-01

    Most biometric books are either extraordinarily technical for technophiles or extremely elementary for the lay person. Striking a balance between the two, Biometric Technology: Authentication, Biocryptography, and Cloud-Based Architecture is ideal for business, IT, or security managers that are faced with the task of making purchasing, migration, or adoption decisions. It brings biometrics down to an understandable level, so that you can immediately begin to implement the concepts discussed.Exploring the technological and social implications of widespread biometric use, the book considers the

  13. Multimodality imaging techniques.

    Science.gov (United States)

    Martí-Bonmatí, Luis; Sopena, Ramón; Bartumeus, Paula; Sopena, Pablo

    2010-01-01

    In multimodality imaging, the need to combine morphofunctional information can be approached by either acquiring images at different times (asynchronous), and fused them through digital image manipulation techniques or simultaneously acquiring images (synchronous) and merging them automatically. The asynchronous post-processing solution presents various constraints, mainly conditioned by the different positioning of the patient in the two scans acquired at different times in separated machines. The best solution to achieve consistency in time and space is obtained by the synchronous image acquisition. There are many multimodal technologies in molecular imaging. In this review we will focus on those multimodality image techniques more commonly used in the field of diagnostic imaging (SPECT-CT, PET-CT) and new developments (as PET-MR). The technological innovations and development of new tracers and smart probes are the main key points that will condition multimodality image and diagnostic imaging professionals' future. Although SPECT-CT and PET-CT are standard in most clinical scenarios, MR imaging has some advantages, providing excellent soft-tissue contrast and multidimensional functional, structural and morphological information. The next frontier is to develop efficient detectors and electronics systems capable of detecting two modality signals at the same time. Not only PET-MR but also MR-US or optic-PET will be introduced in clinical scenarios. Even more, MR diffusion-weighted, pharmacokinetic imaging, spectroscopy or functional BOLD imaging will merge with PET tracers to further increase molecular imaging as a relevant medical discipline. Multimodality imaging techniques will play a leading role in relevant clinical applications. The development of new diagnostic imaging research areas, mainly in the field of oncology, cardiology and neuropsychiatry, will impact the way medicine is performed today. Both clinical and experimental multimodality studies, in

  14. Multimodal Authentication Techniques For Staff Identification And ...

    African Journals Online (AJOL)

    Username, Password, Remember me, or Register ... It helps to overcome limitations of single biometric solutions to reduce the ability for the ... It is best, most efficient, effective and most reliable when Biometric Technique and Magnetic Coded ...

  15. Multimodal Processes Rescheduling

    DEFF Research Database (Denmark)

    Bocewicz, Grzegorz; Banaszak, Zbigniew A.; Nielsen, Peter

    2013-01-01

    Cyclic scheduling problems concerning multimodal processes are usually observed in FMSs producing multi-type parts where the Automated Guided Vehicles System (AGVS) plays a role of a material handling system. Schedulability analysis of concurrently flowing cyclic processes (SCCP) exe-cuted in the......Cyclic scheduling problems concerning multimodal processes are usually observed in FMSs producing multi-type parts where the Automated Guided Vehicles System (AGVS) plays a role of a material handling system. Schedulability analysis of concurrently flowing cyclic processes (SCCP) exe...

  16. BIOMETRIC IDENTITY VERIFICATION IN HEALTH SERVICES: A BIOMETRIC SURVEILLANCE PRACTICE IN TURKEY

    Directory of Open Access Journals (Sweden)

    İlker ŞİRİN

    2014-08-01

    Full Text Available Determination or verification of identity with biometric methods has a widespread use especially at borders for security reasons. Social Security Institution transferred the biometric identity verification practice to health sercives that are provided by private and university hospitals. The risks of the new system considering the privacy of personal data are under debate. Although there are announcements or manuals of Social Security Institution regarding the implementation and legislation for data sharing and security exists, lack of a national data protection law brings with it security gaps.

  17. Temporal stability of visual search-driven biometrics

    Science.gov (United States)

    Yoon, Hong-Jun; Carmichael, Tandy R.; Tourassi, Georgia

    2015-03-01

    Previously, we have shown the potential of using an individual's visual search pattern as a possible biometric. That study focused on viewing images displaying dot-patterns with different spatial relationships to determine which pattern can be more effective in establishing the identity of an individual. In this follow-up study we investigated the temporal stability of this biometric. We performed an experiment with 16 individuals asked to search for a predetermined feature of a random-dot pattern as we tracked their eye movements. Each participant completed four testing sessions consisting of two dot patterns repeated twice. One dot pattern displayed concentric circles shifted to the left or right side of the screen overlaid with visual noise, and participants were asked which side the circles were centered on. The second dot-pattern displayed a number of circles (between 0 and 4) scattered on the screen overlaid with visual noise, and participants were asked how many circles they could identify. Each session contained 5 untracked tutorial questions and 50 tracked test questions (200 total tracked questions per participant). To create each participant's "fingerprint", we constructed a Hidden Markov Model (HMM) from the gaze data representing the underlying visual search and cognitive process. The accuracy of the derived HMM models was evaluated using cross-validation for various time-dependent train-test conditions. Subject identification accuracy ranged from 17.6% to 41.8% for all conditions, which is significantly higher than random guessing (1/16 = 6.25%). The results suggest that visual search pattern is a promising, temporally stable personalized fingerprint of perceptual organization.

  18. Temporal Stability of Visual Search-Driven Biometrics

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Hong-Jun [ORNL; Carmichael, Tandy [Tennessee Technological University; Tourassi, Georgia [ORNL

    2015-01-01

    Previously, we have shown the potential of using an individual s visual search pattern as a possible biometric. That study focused on viewing images displaying dot-patterns with different spatial relationships to determine which pattern can be more effective in establishing the identity of an individual. In this follow-up study we investigated the temporal stability of this biometric. We performed an experiment with 16 individuals asked to search for a predetermined feature of a random-dot pattern as we tracked their eye movements. Each participant completed four testing sessions consisting of two dot patterns repeated twice. One dot pattern displayed concentric circles shifted to the left or right side of the screen overlaid with visual noise, and participants were asked which side the circles were centered on. The second dot-pattern displayed a number of circles (between 0 and 4) scattered on the screen overlaid with visual noise, and participants were asked how many circles they could identify. Each session contained 5 untracked tutorial questions and 50 tracked test questions (200 total tracked questions per participant). To create each participant s "fingerprint", we constructed a Hidden Markov Model (HMM) from the gaze data representing the underlying visual search and cognitive process. The accuracy of the derived HMM models was evaluated using cross-validation for various time-dependent train-test conditions. Subject identification accuracy ranged from 17.6% to 41.8% for all conditions, which is significantly higher than random guessing (1/16 = 6.25%). The results suggest that visual search pattern is a promising, fairly stable personalized fingerprint of perceptual organization.

  19. On the Design of Forgiving Biometric Security Systems

    Science.gov (United States)

    Phan, Raphael C.-W.; Whitley, John N.; Parish, David J.

    This work aims to highlight the fundamental issue surrounding biometric security systems: it’s all very nice until a biometric is forged, but what do we do after that? Granted, biometric systems are by physical nature supposedly much harder to forge than other factors of authentication since biometrics on a human body are by right unique to the particular human person. Yet it is also due to this physical nature that makes it much more catastrophic when a forgery does occur, because it implies that this uniqueness has been forged as well, threatening the human individuality; and since crime has by convention relied on identifying suspects by biometric characteristics, loss of this biometric uniqueness has devastating consequences on the freedom and basic human rights of the victimized individual. This uniqueness forgery implication also raises the motivation on the adversary to forge since a successful forgery leads to much more impersonation situations when biometric systems are used i.e. physical presence at crime scenes, identification and access to security systems and premises, access to financial accounts and hence the ability to use the victim’s finances. Depending on the gains, a desperate highly motivated adversary may even resort to directly obtaining the victim’s biometric parts by force e.g. severing the parts from the victim’s body; this poses a risk and threat not just to the individual’s uniqueness claim but also to personal safety and well being. One may then wonder if it is worth putting one’s assets, property and safety into the hands of biometrics based systems when the consequences of biometric forgery far outweigh the consequences of system compromises when no biometrics are used.

  20. Multimode optical fiber

    Science.gov (United States)

    Bigot-Astruc, Marianne; Molin, Denis; Sillard, Pierre

    2014-11-04

    A depressed graded-index multimode optical fiber includes a central core, an inner depressed cladding, a depressed trench, an outer depressed cladding, and an outer cladding. The central core has an alpha-index profile. The depressed claddings limit the impact of leaky modes on optical-fiber performance characteristics (e.g., bandwidth, core size, and/or numerical aperture).

  1. Multimodal training between agents

    DEFF Research Database (Denmark)

    Rehm, Matthias

    2003-01-01

    In the system Locator1, agents are treated as individual and autonomous subjects that are able to adapt to heterogenous user groups. Applying multimodal information from their surroundings (visual and linguistic), they acquire the necessary concepts for a successful interaction. This approach has...

  2. Multimodal news framing effects

    NARCIS (Netherlands)

    Powell, T.E.

    2017-01-01

    Visuals in news media play a vital role in framing citizens’ political preferences. Yet, compared to the written word, visual images are undervalued in political communication research. Using framing theory, this thesis redresses the balance by studying the combined, or multimodal, effects of visual

  3. Multimodal Strategies of Theorization

    DEFF Research Database (Denmark)

    Cartel, Melodie; Colombero, Sylvain; Boxenbaum, Eva

    This paper examines the role of multimodal strategies in processes of theorization. Empirically, we investigate the theorization process of a highly disruptive innovation in the history of architecture: reinforced concrete. Relying on archival data from a dominant French architectural journal from...... with well-known rhetorical strategies and develop a process model of theorization....

  4. Combining Biometric Fractal Pattern and Particle Swarm Optimization-Based Classifier for Fingerprint Recognition

    Directory of Open Access Journals (Sweden)

    Chia-Hung Lin

    2010-01-01

    Full Text Available This paper proposes combining the biometric fractal pattern and particle swarm optimization (PSO-based classifier for fingerprint recognition. Fingerprints have arch, loop, whorl, and accidental morphologies, and embed singular points, resulting in the establishment of fingerprint individuality. An automatic fingerprint identification system consists of two stages: digital image processing (DIP and pattern recognition. DIP is used to convert to binary images, refine out noise, and locate the reference point. For binary images, Katz's algorithm is employed to estimate the fractal dimension (FD from a two-dimensional (2D image. Biometric features are extracted as fractal patterns using different FDs. Probabilistic neural network (PNN as a classifier performs to compare the fractal patterns among the small-scale database. A PSO algorithm is used to tune the optimal parameters and heighten the accuracy. For 30 subjects in the laboratory, the proposed classifier demonstrates greater efficiency and higher accuracy in fingerprint recognition.

  5. Eye safety related to near infrared radiation exposure to biometric devices.

    Science.gov (United States)

    Kourkoumelis, Nikolaos; Tzaphlidou, Margaret

    2011-03-01

    Biometrics has become an emerging field of technology due to its intrinsic security features concerning the identification of individuals by means of measurable biological characteristics. Two of the most promising biometric modalities are iris and retina recognition, which primarily use nonionizing radiation in the infrared region. Illumination of the eye is achieved by infrared light emitting diodes (LEDs). Even if few LED sources are capable of causing direct eye damage as they emit incoherent light, there is a growing concern about the possible use of LED arrays that might pose a potential threat. Exposure to intense coherent infrared radiation has been proven to have significant effects on living tissues. The purpose of this study is to explore the biological effects arising from exposing the eye to near infrared radiation with reference to international legislation.

  6. Robust and Secure Watermarking Using Sparse Information of Watermark for Biometric Data Protection

    Directory of Open Access Journals (Sweden)

    Rohit M Thanki

    2016-08-01

    Full Text Available Biometric based human authentication system is used for security purpose in many organizations in the present world. This biometric authentication system has several vulnerable points. Two of vulnerable points are protection of biometric templates at system database and protection of biometric templates at communication channel between two modules of biometric authentication systems. In this paper proposed a robust watermarking scheme using the sparse information of watermark biometric to secure vulnerable point like protection of biometric templates at the communication channel of biometric authentication systems. A compressive sensing theory procedure is used for generation of sparse information on watermark biometric data using detail wavelet coefficients. Then sparse information of watermark biometric data is embedded into DCT coefficients of host biometric data. This proposed scheme is robust to common signal processing and geometric attacks like JPEG compression, adding noise, filtering, and cropping, histogram equalization. This proposed scheme has more advantages and high quality measures compared to existing schemes in the literature.

  7. Biometric Security for Cell Phones

    Directory of Open Access Journals (Sweden)

    2009-01-01

    Full Text Available Cell phones are already prime targets for theft. The increasing functionality of cell phones is making them even more attractive. With the increase of cell phone functionality including personal digital assistance, banking, e-commerce, remote work, internet access and entertainment, more and more confidential data is stored on these devices. What is protecting this confidential data stored on cell phones? Studies have shown that even though most of the cell phone users are aware of the PIN security feature more than 50% of them are not using it either because of the lack of confidence in it or because of the inconvenience. A large majority of those users believes that an alternative approach to security would be a good idea.

  8. Multi-biometric Liveness Detection – A New Perspective

    African Journals Online (AJOL)

    2016-12-01

    Dec 1, 2016 ... Basic Multi-biometric Authentication System was thought to have sealed the vulnerabilities ..... action of a real physical human being and not from a pattern ... of authentication is referred to as multi-biometric fusion, and such a ...

  9. Efficient and privacy-preserving biometric identification in cloud

    Directory of Open Access Journals (Sweden)

    Changhee Hahn

    2016-09-01

    Full Text Available With the rapid growth in the development of smart devices equipped with biometric sensors, client identification system using biometric traits are widely adopted across various applications. Among many biometric traits, fingerprint-based identification systems have been extensively studied and deployed. However, to adopt biometric identification systems in practical applications, two main obstacles in terms of efficiency and client privacy must be resolved simultaneously. That is, identification should be performed at an acceptable time, and only a client should have access to his/her biometric traits, which are not revocable if leaked. Until now, multiple studies have demonstrated successful protection of client biometric data; however, such systems lack efficiency that leads to excessive time utilization for identification. The most recently researched scheme shows efficiency improvements but reveals client biometric traits to other entities such as biometric database server. This violates client privacy. In this paper, we propose an efficient and privacy-preserving fingerprint identification scheme by using cloud systems. The proposed scheme extensively exploits the computation power of a cloud so that most of the laborious computations are performed by the cloud service provider. According to our experimental results on an Amazon EC2 cloud, the proposed scheme is faster than the existing schemes and guarantees client privacy by exploiting symmetric homomorphic encryption. Our security analysis shows that during identification, the client fingerprint data is not disclosed to the cloud service provider or fingerprint database server.

  10. Forensic biometrics: From two communities to one discipline

    NARCIS (Netherlands)

    Meuwly, Didier; Meuwly, Didier; Veldhuis, Raymond N.J.

    2012-01-01

    This article describes how the fields of biometrics and forensic science can contribute and benefit from each other. The aim is to foster the development of new methods and tools improving the current forensic biometric applications and allowing for the creation of new ones. The article begins with

  11. 21 CFR 1311.116 - Additional requirements for biometrics.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 9 2010-04-01 2010-04-01 false Additional requirements for biometrics. 1311.116 Section 1311.116 Food and Drugs DRUG ENFORCEMENT ADMINISTRATION, DEPARTMENT OF JUSTICE REQUIREMENTS FOR... for biometrics. (a) If one of the factors used to authenticate to the electronic prescription...

  12. Biometrical analysis in radiobiological works of N.V. Luchnik

    International Nuclear Information System (INIS)

    Glotov, N.V.

    1996-01-01

    The contribution of the famous Russian geneticist and biophysics N.V. Luchnik into biometrical analysis of radiobiological data is discussed. His works on radiation mortality of mice (2) and the process of post-radiation repair of chromosome aberrations (10) are thoroughly observed. The conclusion of necessity to develop biometrical analysis as separate part of biometry is made

  13. Security analysis for biometric data in ID documents

    NARCIS (Netherlands)

    Schimke, S.; Kiltz, S.; Vielhauer, C.; Kalker, A.A.C.M.

    2005-01-01

    In this paper we analyze chances and challenges with respect to the security of using biometrics in ID documents. We identify goals for ID documents, set by national and international authorities, and discuss the degree of security, which is obtainable with the inclusion of biometric into documents

  14. A study of dorsal vein pattern for biometric security

    African Journals Online (AJOL)

    Nafiisah

    ensure more reliable security, many biometric verification techniques have been developed .... 3.0 HA D DORSAL VEI PATTER AS A BIOMETRIC ... image for the back of the hand, and converted by a computer into a digital image that can be.

  15. Semiparametric copula models for biometric score level fusion

    NARCIS (Netherlands)

    Susyanto, N.

    2016-01-01

    In biometric recognition, biometric samples (images of faces, fingerprints, voices, gaits, etc.) of people are compared and matchers (classifiers) indicate the level of similarity between any pair of samples by a score. If we model the joint distribution of all scores by a (semiparametric) Gaussian

  16. Multimodal 2D Brain Computer Interface.

    Science.gov (United States)

    Almajidy, Rand K; Boudria, Yacine; Hofmann, Ulrich G; Besio, Walter; Mankodiya, Kunal

    2015-08-01

    In this work we used multimodal, non-invasive brain signal recording systems, namely Near Infrared Spectroscopy (NIRS), disc electrode electroencephalography (EEG) and tripolar concentric ring electrodes (TCRE) electroencephalography (tEEG). 7 healthy subjects participated in our experiments to control a 2-D Brain Computer Interface (BCI). Four motor imagery task were performed, imagery motion of the left hand, the right hand, both hands and both feet. The signal slope (SS) of the change in oxygenated hemoglobin concentration measured by NIRS was used for feature extraction while the power spectrum density (PSD) of both EEG and tEEG in the frequency band 8-30Hz was used for feature extraction. Linear Discriminant Analysis (LDA) was used to classify different combinations of the aforementioned features. The highest classification accuracy (85.2%) was achieved by using features from all the three brain signals recording modules. The improvement in classification accuracy was highly significant (p = 0.0033) when using the multimodal signals features as compared to pure EEG features.

  17. On humanitarian refugee biometrics and new forms of intervention

    DEFF Research Database (Denmark)

    Jacobsen, Katja Lindskov

    2017-01-01

    This article traces a development from UNHCR's initial use of biometrics in a few pilot projects (early/mid-2000s), to the emergence of a UNHCR policy where biometric registration is considered a "strategic decision". Next it engages key insights from current debates about 'materiality' and agentic...... capacity in combination with current debates about new forms of intervention. Finally, these insights are combined into a framework through which the last part of the article engages critically with this development of humanitarian refugee biometrics by posing the following question: how does an approach...... biometric refugee data, has affected the relationship between UNHCR, donor states, host states and refugees, the article shows how UNHCR's trialling of new biometric technologies, combined with actual and potential data-sharing practices, has advanced the technology's performance as well as its...

  18. [Personal identification with biometric and genetic methods].

    Science.gov (United States)

    Cabanis, Emmanuel-Alain; Le Gall, Jean-Yves; Ardaillou, Raymond

    2007-11-01

    The need for personal identification is growing in many avenues of society. To "identify" a person is to establish a link between his or her observed characteristics and those previously stored in a database. To "authenticate" is to decide whether or not someone is the person he or she claims to be. These two objectives can now be achieved by analysing biometric data and genetic prints. All biometric techniques proceed in several stages: acquisition of an image or physical parameters, encoding them with a mathematical model, comparing the results of this model with those contained in the database, and calculating the error risk. These techniques must be usable worldwide and must examine specific and permanent personal data. The most widely used are facial recognition, digital prints (flexion folds and dermatoglyphs, that offer the advantage of leaving marks), and the surface and texture of the iris. Other biometric techniques analyse behaviours such as walking, signing, typing, or speaking. Implanted radio-transmitters are another means of identification. All these systems are evaluated on the basis of the same parameters, namely the false rejection rate, the false acceptance rate, and the failure-to-enrol rate. The uses of biometrics are increasing and diversifying, and now include national and international identification systems, control of access to protected sites, criminal and victim identification, and transaction security. Genetic methods can identify individuals almost infallibly, based on short tandem repeats of 2-5 nucleotides, or microsatellites. The most recent kits analyze 11-16 independent autosomal markers. Mitochondrial DNA and Y chromosome DNA can also be analyzed. These genetic tests are currently used to identify suspected criminals or their victims from biological samples, and to establish paternity. Personal identification raises many ethical questions, however, such as when to create and how to use a database while preserving personal freedom

  19. Biometry, biometrics, biostatistics, bioinformatics,..., bio-X.

    Science.gov (United States)

    Molenberghs, Geert

    2005-03-01

    Recent scientific evolutions force us to rethink our profession's position on the scientific map, in relation to our neighboring professions, the ones with which we traditionally have strong collaborative links as well as the newly emerging fields, but also within our own, diverse professional group. We will show that great inspiration can be drawn from our own history, in fact from the early days of the Society. A recent inspiring example has been set by the late Rob Kempton, who died suddenly just months before he was to become President of the International Biometric Society.

  20. Biometrics and Psychometrics: Origins, Commonalities and Differences

    Directory of Open Access Journals (Sweden)

    John Gower

    2016-09-01

    Full Text Available Starting with the common origins of biometrics and psychometrics at the beginning of the twentieth century, the paper compares and contrasts subsequent developments, informed by the author's 35 years at Rothamsted Experimental Station followed by a period with the data theory group in Leiden and thereafter. Although the methods used by biometricians and psychometricians have much in common, there are important differences arising from the different fields of study. Similar differences arise wherever data are generated and may be regarded as a major driving force in the development of statistical ideas.

  1. Secure Biometric E-Voting Scheme

    Science.gov (United States)

    Ahmed, Taha Kh.; Aborizka, Mohamed

    The implementation of the e-voting becomes more substantial with the rapid increase of e-government development. The recent growth in communications and cryptographic techniques facilitate the implementation of e-voting. Many countries introduced e-voting systems; unfortunately most of these systems are not fully functional. In this paper we will present an e-voting scheme that covers most of the e-voting requirements, smart card and biometric recognition technology were implemented to guarantee voter's privacy and authentication.

  2. Biometric verificaton and biometric identification of a person by methods of statistical analysis of digitized iris images

    Czech Academy of Sciences Publication Activity Database

    Machala, L.; Pospíšil, Jaroslav

    40-41, - (2001), s. 155-162 ISSN 0231-9365 Institutional research plan: CEZ:AV0Z1010921 Keywords : biometric verification * biometric idntification * human eye`s iris * statistical error of type I * statistical erroer II * charasteristic iris vector Subject RIV: BH - Optics, Masers, Lasers

  3. Contemporary Multi-Modal Historical Representations and the Teaching of Disciplinary Understandings in History

    Science.gov (United States)

    Donnelly, Debra J.

    2018-01-01

    Traditional privileging of the printed text has been considerably eroded by rapid technological advancement and in Australia, as elsewhere, many History teaching programs feature an array of multi-modal historical representations. Research suggests that engagement with the visual and multi-modal constructs has the potential to enrich the pedagogy…

  4. Supporting the Maritime Information Dominance: Optimizing Tactical Network for Biometric Data Sharing in Maritime Interdiction Operations

    Science.gov (United States)

    2015-03-01

    biometric data collection. Capture role- player mock biometric data including finger prints, iris scans, and facial recognition photos. (MOC training...MARITIME INFORMATION DOMINANCE: OPTIMIZING TACTICAL NETWORK FOR BIOMETRIC DATA SHARING IN MARITIME INTERDICTION OPERATIONS by Adam R. Sinsel...MARITIME INFORMATION DOMINANCE: OPTIMIZING TACTICAL NETWORK FOR BIOMETRIC DATA SHARING IN MARITIME INTERDICTION OPERATIONS 6. AUTHOR(S) Adam R

  5. Privacy leakage in binary biometric systems : from gaussian to binary data

    NARCIS (Netherlands)

    Ignatenko, T.; Willems, F.M.J.; Campisi, P.

    2013-01-01

    In this chapter we investigate biometric key-binding systems for i.i.d. Gaussian biometric sources. In these systems two terminals observe two correlated biometric sequences. Moreover, a secret key, which is independent of the biometric sequences, is selected at the first terminal. The first

  6. Multimodal mechanisms of food creaminess sensation.

    Science.gov (United States)

    Chen, Jianshe; Eaton, Louise

    2012-12-01

    In this work, the sensory creaminess of a set of four viscosity-matched fluid foods (single cream, evaporated milk, corn starch solution, and corn starch solution containing long chain free fatty acids) was tested by a panel of 16 assessors via controlled sensation mechanisms of smell only, taste only, taste and tactile, and integrated multimodal. It was found that all sensation channels were able to discriminate between creamy and non-creamy foods, but only the multimodal method gave creaminess ratings in agreement with the samples' fat content. Results from this study show that the presence of long chain free fatty acids has no influence on creaminess perception. It is certain that food creaminess is not a primary sensory property but an integrated sensory perception (or sensory experience) derived from combined sensations of visual, olfactory, gustatory, and tactile cues. Creamy colour, milky flavour, and smooth texture are probably the most important sensory features of food creaminess.

  7. Biometric Authentication for Gender Classification Techniques: A Review

    Science.gov (United States)

    Mathivanan, P.; Poornima, K.

    2017-12-01

    One of the challenging biometric authentication applications is gender identification and age classification, which captures gait from far distance and analyze physical information of the subject such as gender, race and emotional state of the subject. It is found that most of the gender identification techniques have focused only with frontal pose of different human subject, image size and type of database used in the process. The study also classifies different feature extraction process such as, Principal Component Analysis (PCA) and Local Directional Pattern (LDP) that are used to extract the authentication features of a person. This paper aims to analyze different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm. Therefore, it helps in developing a novel gender classification algorithm with less computation cost and more accuracy. In this paper, an overview and classification of different gender identification techniques are first presented and it is compared with other existing human identification system by means of their performance.

  8. Gestures and multimodal input

    OpenAIRE

    Keates, Simeon; Robinson, Peter

    1999-01-01

    For users with motion impairments, the standard keyboard and mouse arrangement for computer access often presents problems. Other approaches have to be adopted to overcome this. In this paper, we will describe the development of a prototype multimodal input system based on two gestural input channels. Results from extensive user trials of this system are presented. These trials showed that the physical and cognitive loads on the user can quickly become excessive and detrimental to the interac...

  9. Biometric Authentication Using the PPG: A Long-Term Feasibility Study

    Directory of Open Access Journals (Sweden)

    Jorge Sancho

    2018-05-01

    Full Text Available The photoplethysmogram (PPG is a biomedical signal that can be used to estimate volumetric blood flow changes in the peripheral circulation. During the past few years, several works have been published in order to assess the potential for PPGs to be used in biometric authentication systems, but results are inconclusive. In this paper we perform an analysis of the feasibility of using the PPG as a realistic biometric alternative in the long term. Several feature extractors (based on the time domain and the Karhunen–Loève transform and matching metrics (Manhattan and Euclidean distances have been tested using four different PPG databases (PRRB, MIMIC-II, Berry, and Nonin. We show that the false match rate (FMR and false non-match rate (FNMR values remain constant in different time instances for a selected threshold, which is essential for using the PPG for biometric authentication purposes. On the other hand, obtained equal error rate (EER values for signals recorded during the same session range from 1.0% for high-quality signals recorded in controlled conditions to 8% for those recorded in conditions closer to real-world scenarios. Moreover, in certain scenarios, EER values rise up to 23.2% for signals recorded over different days, signaling that performance degradation could take place with time.

  10. Towards fraud-proof ID documents using multiple data hiding technologies and biometrics

    Science.gov (United States)

    Picard, Justin; Vielhauer, Claus; Thorwirth, Niels

    2004-06-01

    Identity documents, such as ID cards, passports, and driver's licenses, contain textual information, a portrait of the legitimate holder, and eventually some other biometric characteristics such as a fingerprint or handwritten signature. As prices for digital imaging technologies fall, making them more widely available, we have seen an exponential increase in the ease and the number of counterfeiters that can effectively forge documents. Today, with only limited knowledge of technology and a small amount of money, a counterfeiter can effortlessly replace a photo or modify identity information on a legitimate document to the extent that it is very diffcult to differentiate from the original. This paper proposes a virtually fraud-proof ID document based on a combination of three different data hiding technologies: digital watermarking, 2-D bar codes, and Copy Detection Pattern, plus additional biometric protection. As will be shown, that combination of data hiding technologies protects the document against any forgery, in principle without any requirement for other security features. To prevent a genuine document to be used by an illegitimate user,biometric information is also covertly stored in the ID document, to be used for identification at the detector.

  11. High Resolution Ultrasonic Method for 3D Fingerprint Representation in Biometrics

    Science.gov (United States)

    Maev, R. Gr.; Bakulin, E. Y.; Maeva, E. Y.; Severin, F. M.

    Biometrics is an important field which studies different possible ways of personal identification. Among a number of existing biometric techniques fingerprint recognition stands alone - because very large database of fingerprints has already been acquired. Also, fingerprints are an important evidence that can be collected at a crime scene. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. Ultrasonic method of fingerprint imaging was originally introduced over a decade as the mapping of the reflection coefficient at the interface between the finger and a covering plate and has shown very good reliability and free from imperfections of previous two methods. This work introduces a newer development of the ultrasonic fingerprint imaging, focusing on the imaging of the internal structures of fingerprints (including sweat pores) with raw acoustic resolution of about 500 dpi (0.05 mm) using a scanning acoustic microscope to obtain images and acoustic data in the form of 3D data array. C-scans from different depths inside the fingerprint area of fingers of several volunteers were obtained and showed good contrast of ridges-and-valleys patterns and practically exact correspondence to the standard ink-and-paper prints of the same areas. Important feature reveled on the acoustic images was the clear appearance of the sweat pores, which could provide additional means of identification.

  12. Biometric Authentication Using the PPG: A Long-Term Feasibility Study.

    Science.gov (United States)

    Sancho, Jorge; Alesanco, Álvaro; García, José

    2018-05-11

    The photoplethysmogram (PPG) is a biomedical signal that can be used to estimate volumetric blood flow changes in the peripheral circulation. During the past few years, several works have been published in order to assess the potential for PPGs to be used in biometric authentication systems, but results are inconclusive. In this paper we perform an analysis of the feasibility of using the PPG as a realistic biometric alternative in the long term. Several feature extractors (based on the time domain and the Karhunen⁻Loève transform) and matching metrics (Manhattan and Euclidean distances) have been tested using four different PPG databases (PRRB, MIMIC-II, Berry, and Nonin). We show that the false match rate ( FMR ) and false non-match rate ( FNMR ) values remain constant in different time instances for a selected threshold, which is essential for using the PPG for biometric authentication purposes. On the other hand, obtained equal error rate (EER) values for signals recorded during the same session range from 1.0% for high-quality signals recorded in controlled conditions to 8% for those recorded in conditions closer to real-world scenarios. Moreover, in certain scenarios, EER values rise up to 23.2% for signals recorded over different days, signaling that performance degradation could take place with time.

  13. Device for biometric verification of maternity

    Directory of Open Access Journals (Sweden)

    Lalović Komlen

    2015-01-01

    Full Text Available Biometry is the scientific discipline and technology that measures and analyzes physiological or behavioral characteristics of people and is widely deployed in modern society security systems. Device for biometric identification of maternity is a dual fingerprint scanner that acquires fingerprint templates of the mother and the child at the very moment of birth, generates unique ID reference, and further guarantees mother-child relationship with that reference. Technical issue that is solved with this work and the proposed device is scanning, processing, and storing encrypted biometric templates with a goal to provide a 100% guarantee maternity for each new born child. Scanning the fingerprints of both mother and the child simultaneously, at moment of birth, and pairing them with unique ID reference removes potential fears occurring from hospital negligence to malicious activities, while the data encryption raises the whole process to the highest level of security and confidentiality. The main contribution of the device that removes the fear that almost every mother has in this period as it provides an answer to the question: “Is this my baby?” with a 100% guarantee “It’s certainly yours!”

  14. A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition

    Directory of Open Access Journals (Sweden)

    Shahram Najam

    2018-01-01

    Full Text Available A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis and K-NN (K-Nearest Neighbor. It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition.

  15. A novel hybrid biometric electronic voting system: integrating finger print face recognition

    International Nuclear Information System (INIS)

    Najam, S.S.; Shaikh, A.Z.; Naqvi, S.

    2018-01-01

    A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis) and K-NN (K-Nearest Neighbor). It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition. (author)

  16. Design and implementation of an algorithm for creating templates for the purpose of iris biometric authentication through the analysis of textures implemented on a FPGA

    International Nuclear Information System (INIS)

    Giacometto, F J; Vilardy, J M; Torres, C O; Mattos, L

    2011-01-01

    Currently addressing problems related to security in access control, as a consequence, have been developed applications that work under unique characteristics in individuals, such as biometric features. In the world becomes important working with biometric images such as the liveliness of the iris which are for both the pattern of retinal images as your blood vessels. This paper presents an implementation of an algorithm for creating templates for biometric authentication with ocular features for FPGA, in which the object of study is that the texture pattern of iris is unique to each individual. The authentication will be based in processes such as edge extraction methods, segmentation principle of John Daugman and Libor Masek's, and standardization to obtain necessary templates for the search of matches in a database and then get the expected results of authentication.

  17. Design and implementation of an algorithm for creating templates for the purpose of iris biometric authentication through the analysis of textures implemented on a FPGA

    Energy Technology Data Exchange (ETDEWEB)

    Giacometto, F J; Vilardy, J M; Torres, C O; Mattos, L, E-mail: franciscogiacometto@unicesar.edu.co [Laboratorio de Optica e Informatica, Universidad Popular del Cesar, Sede balneario Hurtado, Valledupar, Cesar (Colombia)

    2011-01-01

    Currently addressing problems related to security in access control, as a consequence, have been developed applications that work under unique characteristics in individuals, such as biometric features. In the world becomes important working with biometric images such as the liveliness of the iris which are for both the pattern of retinal images as your blood vessels. This paper presents an implementation of an algorithm for creating templates for biometric authentication with ocular features for FPGA, in which the object of study is that the texture pattern of iris is unique to each individual. The authentication will be based in processes such as edge extraction methods, segmentation principle of John Daugman and Libor Masek's, and standardization to obtain necessary templates for the search of matches in a database and then get the expected results of authentication.

  18. Biometric parameters in different stages of primary angle closure using low-coherence interferometry.

    Science.gov (United States)

    Yazdani, Shahin; Akbarian, Shadi; Pakravan, Mohammad; Doozandeh, Azadeh; Afrouzifar, Mohsen

    2015-03-01

    To compare ocular biometric parameters using low-coherence interferometry among siblings affected with different degrees of primary angle closure (PAC). In this cross-sectional comparative study, a total of 170 eyes of 86 siblings from 47 families underwent low-coherence interferometry (LenStar 900; Haag-Streit, Koeniz, Switzerland) to determine central corneal thickness, anterior chamber depth (ACD), aqueous depth (AD), lens thickness (LT), vitreous depth, and axial length (AL). Regression coefficients were applied to show the trend of the measured variables in different stages of angle closure. To evaluate the discriminative power of the parameters, receiver operating characteristic curves were used. Best cutoff points were selected based on the Youden index. Sensitivity, specificity, positive and negative predicative values, positive and negative likelihood ratios, and diagnostic accuracy were determined for each variable. All biometric parameters changed significantly from normal eyes to PAC suspects, PAC, and PAC glaucoma; there was a significant stepwise decrease in central corneal thickness, ACD, AD, vitreous depth, and AL, and an increase in LT and LT/AL. Anterior chamber depth and AD had the best diagnostic power for detecting angle closure; best levels of sensitivity and specificity were obtained with cutoff values of 3.11 mm for ACD and 2.57 mm for AD. Biometric parameters measured by low-coherence interferometry demonstrated a significant and stepwise change among eyes affected with various degrees of angle closure. Although the current classification scheme for angle closure is based on anatomical features, it has excellent correlation with biometric parameters.

  19. Biometric iris image acquisition system with wavefront coding technology

    Science.gov (United States)

    Hsieh, Sheng-Hsun; Yang, Hsi-Wen; Huang, Shao-Hung; Li, Yung-Hui; Tien, Chung-Hao

    2013-09-01

    Biometric signatures for identity recognition have been practiced for centuries. Basically, the personal attributes used for a biometric identification system can be classified into two areas: one is based on physiological attributes, such as DNA, facial features, retinal vasculature, fingerprint, hand geometry, iris texture and so on; the other scenario is dependent on the individual behavioral attributes, such as signature, keystroke, voice and gait style. Among these features, iris recognition is one of the most attractive approaches due to its nature of randomness, texture stability over a life time, high entropy density and non-invasive acquisition. While the performance of iris recognition on high quality image is well investigated, not too many studies addressed that how iris recognition performs subject to non-ideal image data, especially when the data is acquired in challenging conditions, such as long working distance, dynamical movement of subjects, uncontrolled illumination conditions and so on. There are three main contributions in this paper. Firstly, the optical system parameters, such as magnification and field of view, was optimally designed through the first-order optics. Secondly, the irradiance constraints was derived by optical conservation theorem. Through the relationship between the subject and the detector, we could estimate the limitation of working distance when the camera lens and CCD sensor were known. The working distance is set to 3m in our system with pupil diameter 86mm and CCD irradiance 0.3mW/cm2. Finally, We employed a hybrid scheme combining eye tracking with pan and tilt system, wavefront coding technology, filter optimization and post signal recognition to implement a robust iris recognition system in dynamic operation. The blurred image was restored to ensure recognition accuracy over 3m working distance with 400mm focal length and aperture F/6.3 optics. The simulation result as well as experiment validates the proposed code

  20. A multimodal parallel architecture: A cognitive framework for multimodal interactions.

    Science.gov (United States)

    Cohn, Neil

    2016-01-01

    Human communication is naturally multimodal, and substantial focus has examined the semantic correspondences in speech-gesture and text-image relationships. However, visual narratives, like those in comics, provide an interesting challenge to multimodal communication because the words and/or images can guide the overall meaning, and both modalities can appear in complicated "grammatical" sequences: sentences use a syntactic structure and sequential images use a narrative structure. These dual structures create complexity beyond those typically addressed by theories of multimodality where only a single form uses combinatorial structure, and also poses challenges for models of the linguistic system that focus on single modalities. This paper outlines a broad theoretical framework for multimodal interactions by expanding on Jackendoff's (2002) parallel architecture for language. Multimodal interactions are characterized in terms of their component cognitive structures: whether a particular modality (verbal, bodily, visual) is present, whether it uses a grammatical structure (syntax, narrative), and whether it "dominates" the semantics of the overall expression. Altogether, this approach integrates multimodal interactions into an existing framework of language and cognition, and characterizes interactions between varying complexity in the verbal, bodily, and graphic domains. The resulting theoretical model presents an expanded consideration of the boundaries of the "linguistic" system and its involvement in multimodal interactions, with a framework that can benefit research on corpus analyses, experimentation, and the educational benefits of multimodality. Copyright © 2015.