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Int. J. Biom.最新文献

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Extraction and selection of binarised statistical image features for fingerprint recognition 指纹识别中二值化统计图像特征的提取与选择
Int. J. Biom. Pub Date : 2017-05-15 DOI: 10.1504/IJBM.2017.10005054
A. Adjimi, Abdenour Hacine-Gharbi, P. Ravier, M. Mostefai
{"title":"Extraction and selection of binarised statistical image features for fingerprint recognition","authors":"A. Adjimi, Abdenour Hacine-Gharbi, P. Ravier, M. Mostefai","doi":"10.1504/IJBM.2017.10005054","DOIUrl":"https://doi.org/10.1504/IJBM.2017.10005054","url":null,"abstract":"Due to their simplicity and efficiency, histogram-based descriptors are very used in the task of fingerprint recognition. In this work, we use a novel histogram based descriptor called binarised statistical image features (BSIF). The experiments have conducted on the standard FVC2002 database. We have extracted the BSIF histograms from sub-images around the core point of the fingerprint image and concatenated them to construct the final features vector. The experiments have shown that an increasing number of extracted sub-images lead to an increasing recognition rate, but lead also to higher dimension histogram which decreased performance of the system regarding computing time and memory capacity. To avoid this problem we have used a feature selection method based on the mutual information called interaction capping (ICAP) which selects the relevant bins of the BSIF histogram. The results showed that using feature selection method could reduce the dimensionality leading to a less computational complexity.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116959690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Approach to cryptographic key generation from fingerprint biometrics 基于指纹生物识别技术的密钥生成方法
Int. J. Biom. Pub Date : 2015-09-01 DOI: 10.1504/IJBM.2015.071946
Subhas Barman, D. Samanta, Samiran Chattopadhyay
{"title":"Approach to cryptographic key generation from fingerprint biometrics","authors":"Subhas Barman, D. Samanta, Samiran Chattopadhyay","doi":"10.1504/IJBM.2015.071946","DOIUrl":"https://doi.org/10.1504/IJBM.2015.071946","url":null,"abstract":"In crypto-biometric system CBS, biometric is combined with cryptography. In CBS, either accessing a cryptographic key is controlled with biometric or the key is generated from biometric features. This work is related to the latter approach in CBS. In such a system, protecting the privacy of the biometric data is an important concern. Further, there is a need to generate different cryptographic keys from the same biometric template of a user. Cancellable transformation of biometric data prior to the key generation is known as a solution. In this paper, we propose an approach to generate cryptographic key from cancellable fingerprint templates C","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130852504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
An embedded system for extracting keystroke patterns using pressure sensors 一种利用压力传感器提取按键模式的嵌入式系统
Int. J. Biom. Pub Date : 2015-09-01 DOI: 10.1504/IJBM.2015.071948
C. Leberknight, M. Recce
{"title":"An embedded system for extracting keystroke patterns using pressure sensors","authors":"C. Leberknight, M. Recce","doi":"10.1504/IJBM.2015.071948","DOIUrl":"https://doi.org/10.1504/IJBM.2015.071948","url":null,"abstract":"Popular biometric security technologies include fingerprint and iris recognition systems. These technologies are extremely accurate because the patterns associated with an individual's finger or eye are very unique and static. However, when these technologies are used for physical access control they inform the potential adversary that specific characteristics are required to gain access. Behaviometrics aims to develop new strategies to enhance physical security via covert monitoring of distinct behavioral patterns. This research presents a novel stand-alone behaviometric prototype that incorporates standard password security with unique pressure characteristics to covertly analyse individual typing patterns. The prototype is evaluated under a controlled setting with 62 human subjects and nine classification algorithms. The kNN algorithm produced the highest classification rate of 94%. This research is one of the few papers that empirically substantiates biometric performance with a large-scale human subject trial, and also identifies several critical design considerations that impact classifier performance.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127295859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Invariant face recognition using Zernike moments combined with feed forward neural network 基于Zernike矩和前馈神经网络的人脸不变性识别
Int. J. Biom. Pub Date : 2015-09-01 DOI: 10.1504/IJBM.2015.071950
Vijayalakshmi G. V. Mahesh, A. Raj
{"title":"Invariant face recognition using Zernike moments combined with feed forward neural network","authors":"Vijayalakshmi G. V. Mahesh, A. Raj","doi":"10.1504/IJBM.2015.071950","DOIUrl":"https://doi.org/10.1504/IJBM.2015.071950","url":null,"abstract":"The paper proposes a face recognition system using Zernike moments ZM and feed forward neural network as a classifier. Magnitudes of the ZM, which are invariant to rotation, are used as feature vectors for efficient representation of the images. The experiment was conducted on the ORL and Texas 3D Face Recognition Database which has both colour and range images. The recognition performance with measures like overall recognition accuracy, false acceptance rate, false rejection rate and true rejection rate was evaluated with multilayer perceptron neural network, radial basis function neural network and probabilistic neural network for variable lengths of the feature vector using confusion matrix. The simulation results indicates that the invariant ZM with neural network classifier was successful in recognising the images constrained to different variations and illumination conditions. The overall classification accuracy of 99.7% with MLPNN and 99.6% with MLPNN was achieved with range images and grey images from Texas 3D Face Recognition Database, respectively. Furthermore, 99.5% accuracy with RBFNN was achieved from ORL database.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115257934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Efficient palmprint identification using novel symmetry filter and alignment refinement 基于新型对称滤波和对齐优化的高效掌纹识别
Int. J. Biom. Pub Date : 2015-09-01 DOI: 10.1504/IJBM.2015.071943
Hoang Thien Van, T. Le, T. Dinh
{"title":"Efficient palmprint identification using novel symmetry filter and alignment refinement","authors":"Hoang Thien Van, T. Le, T. Dinh","doi":"10.1504/IJBM.2015.071943","DOIUrl":"https://doi.org/10.1504/IJBM.2015.071943","url":null,"abstract":"This paper presents a robust algorithm for line orientation code-based palmprint identification in which we propose a novel symmetry filter and an efficient alignment refinement technique. The main idea of the symmetry filter is to compute the approximate magnitude of the Gabor filter based on the modified finite Radon transform MFRAT, the so-called GMFRAT filter. The advantages of GMFRAT filters are that: 1 they are capable of quickly computing orientation codes; 2 they remarkably reduce remarkably the sizes of these features. The alignment refinement technique, which uses local orientation patterns, is also proposed to solve the problem of rotations and translations caused by an imperfect preprocessing phase. Based on our alignment refinement, the matching algorithm is designed. The experimental results obtained using the public databases of the Hong Kong Polytechnic University and the Indian Institute of Technology Delhi demonstrate the effectiveness of the proposed method.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122834522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Face recognition using a novel image representation scheme and multi-scale local features 基于多尺度局部特征的人脸识别方法
Int. J. Biom. Pub Date : 2015-09-01 DOI: 10.1504/IJBM.2015.071941
Qingchuan Tao, Zhiming Liu, G. Bebis, M. Hussain
{"title":"Face recognition using a novel image representation scheme and multi-scale local features","authors":"Qingchuan Tao, Zhiming Liu, G. Bebis, M. Hussain","doi":"10.1504/IJBM.2015.071941","DOIUrl":"https://doi.org/10.1504/IJBM.2015.071941","url":null,"abstract":"This paper presents a new method for improving face recognition performance under difficult conditions. Specifically, a new image representation scheme is proposed which is derived from the YCrQ colour space using principal component analysis PCA followed by Fisher linear discriminant analysis FLDA. A multi-scale local feature, LBP-DWT, is used for face representation which is computed by extracting different resolution local binary patterns LBP features from the new image representation and transforming the LBP features into the wavelet domain using discrete wavelet transform DWT and Haar wavelets. A variant of non-parametric discriminant analysis NDA, called regularised non-parametric discriminant analysis RNDA is introduced to extract the most discriminating features from LBP-DWT. The proposed methodology has been evaluated using two challenging face databases FERET and multi-PIE. The promising experimental results show that the proposed method outperforms two state-of-the-art methods, one based on Gabor features and the other based on sparse representation classification SRC.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116974573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Research of dual-modal decision level fusion for fingerprint and finger vein image 指纹与指静脉图像的双模态决策级融合研究
Int. J. Biom. Pub Date : 2015-09-01 DOI: 10.1504/IJBM.2015.071949
Hui Ma, P. Oluwatoyin, Shu-Li Sun
{"title":"Research of dual-modal decision level fusion for fingerprint and finger vein image","authors":"Hui Ma, P. Oluwatoyin, Shu-Li Sun","doi":"10.1504/IJBM.2015.071949","DOIUrl":"https://doi.org/10.1504/IJBM.2015.071949","url":null,"abstract":"The use of personal identity authentication systems with multi-modal biometrics has been proposed in order to increase the performance and robustness against environmental variation and fraudulent attacks. This paper presents a novel fingerprint and finger vein identity authentication system based on multi-route detection. Firstly, two classifiers are designed for fingerprint image and finger vein image respectively. Then extracted feature vectors from the first stage are then concatenated to make the third classifier. The final result is achieved by the fusion of the three classifiers' recognition results at the decision level. Experimental results show that this algorithm not only overcomes the limitations of single-modal biometrics, but also effectively improves the recognition performance of the system.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128218898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Human Gender Classification: A Review 人类性别分类综述
Int. J. Biom. Pub Date : 2015-07-17 DOI: 10.1504/IJBM.2016.10003589
Feng Lin, Yingxiao Wu, Zhuang Yan, X. Long, Wenyao Xu
{"title":"Human Gender Classification: A Review","authors":"Feng Lin, Yingxiao Wu, Zhuang Yan, X. Long, Wenyao Xu","doi":"10.1504/IJBM.2016.10003589","DOIUrl":"https://doi.org/10.1504/IJBM.2016.10003589","url":null,"abstract":"Gender contains a wide range of information regarding to the characteristics difference between male and female. Successful gender recognition is essential and critical for many applications in the commercial domains such as applications of human-computer interaction and computer-aided physiological or psychological analysis. Some have proposed various approaches for automatic gender classification using the features derived from human bodies and/or behaviors. First, this paper introduces the challenge and application for gender classification research. Then, the development and framework of gender classification are described. Besides, we compare these state-of-the-art approaches, including vision-based methods, biological information-based method, and social network information-based method, to provide a comprehensive review in the area of gender classification. In mean time, we highlight the strength and discuss the limitation of each method. Finally, this review also discusses several promising applications for the future work.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115236798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 61
Biometric signature verification 生物特征签名验证
Int. J. Biom. Pub Date : 2015-07-01 DOI: 10.1504/IJBM.2015.070924
S. Jabin, F. Zareen
{"title":"Biometric signature verification","authors":"S. Jabin, F. Zareen","doi":"10.1504/IJBM.2015.070924","DOIUrl":"https://doi.org/10.1504/IJBM.2015.070924","url":null,"abstract":"In recent years, biometric signature verification BSV has been considered with renewed interest with increasing need of security and individual verification and authentication whether in banks, offices, institutions or other commercial organisations. Biometric signature verification is a behavioural biometric technique as a signature signifies unique behaviour of an individual. It can upgrade online banking using online digital systems for signing which cannot be altered or manipulated. Digital signature pads use algorithms to record the features of the signature, which is used to authenticate a signer during a transaction. This paper aims to present a comprehensive literature survey of the most recent research papers on biometric signature verification. It highlights the most important methods and addresses variations in the methods and features that are being taken up in the most recent research in this field along with the possible extensions.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131814410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Phoneme dependent inter-session variability reduction for speaker verification 针对说话人验证的音素依赖性会话间变异性减少
Int. J. Biom. Pub Date : 2015-07-01 DOI: 10.1504/IJBM.2015.070922
Haoze Lu, Wenbin Zhang, Y. Horiuchi, S. Kuroiwa
{"title":"Phoneme dependent inter-session variability reduction for speaker verification","authors":"Haoze Lu, Wenbin Zhang, Y. Horiuchi, S. Kuroiwa","doi":"10.1504/IJBM.2015.070922","DOIUrl":"https://doi.org/10.1504/IJBM.2015.070922","url":null,"abstract":"GMM-UBM super-vectors will potentially lead to worse modelling for speaker verification due to the inter-session variability, especially when a small amount of training utterances were available. In this study, we propose a phoneme dependent method to suppress the inter-session variability. A speaker's model can be represented by several various phoneme Gaussian mixture models. Each of them covers an individual phoneme whose inter-session variability can be constrained in an inter-session independent subspace constructed by principal component analysis PCA, and it uses corpus uttered by a single speaker that has been recorded over a long period. SVM-based experiments performed using a large corpus, constructed by the National Research Institute of Police Science NRIPS to evaluate Japanese speaker recognition, and demonstrate the improvements gained from the proposed method.","PeriodicalId":262486,"journal":{"name":"Int. J. Biom.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131245475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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