2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)最新文献

A novel approach based brain biometrics: Some preliminary results for individual identification 一种基于脑生物识别的新方法:个体识别的一些初步结果

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949218

K. Aloui, A. Naït-Ali, M. Naceur

引用次数: 13

Signature based Fuzzy Vaults with Boosted Feature Selection 基于签名的模糊库与增强特征选择

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949215

George S. Eskander, R. Sabourin, Eric Granger

{"title":"Signature based Fuzzy Vaults with Boosted Feature Selection","authors":"George S. Eskander, R. Sabourin, Eric Granger","doi":"10.1109/CIBIM.2011.5949215","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949215","url":null,"abstract":"Handwritten signatures are commonly employed in many financial and forensic processes, and secure offline signature verification systems (SV) are required to automate such processes. In this context, bio-cryptography systems based on the handwritten signatures may be considered for enhance security. This paper presents a bio-cryptography system that constructs Fuzzy Vaults (FVs) based on the offline signature images. Boosting Feature Selection is employed to select features while training weak classifiers of offline SV systems. The indexes of selected features correspond to the most stable and discriminant features from a user's signature images, and are used to encode user-specific FVs. A password is employed as a second authentication measure, to further enhance system security. During authentication, a user provides both the signature and the password to decode the FV and decouple his private key. If the FV is correctly decoded, the user is authenticated by the verification system. The proposed FV implementation alleviates the security vulnerabilities of the classical SV systems like template security, repudiation, irrevocability, and bypassing the classification decision. Moreover, simulations performed on a real-world signature verification database (with random, simple, and skilled forgeries) indicate security guarantees against stolen authentication measures. While compromised signatures or passwords lead to complete fail (FAR = 100%) of the classical SV or password protected cryptography systems respectively, compromised signatures lead to FAR of 0.1%, and compromised passwords leads to FAR of 15% with the proposed system.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114795834","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: 15

Analysis of template update strategies for keystroke dynamics 击键动力学的模板更新策略分析

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949216

R. Giot, B. Dorizzi, C. Rosenberger

引用次数: 39

Polar fusion technique analysis for evaluating the performances of image fusion of thermal and visual images for human face recognition 基于极化融合技术的人脸识别热图像与视觉图像融合性能评价分析

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949220

M. Bhowmik, D. Bhattacharjee, D. K. Basu, M. Nasipuri

{"title":"Polar fusion technique analysis for evaluating the performances of image fusion of thermal and visual images for human face recognition","authors":"M. Bhowmik, D. Bhattacharjee, D. K. Basu, M. Nasipuri","doi":"10.1109/CIBIM.2011.5949220","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949220","url":null,"abstract":"This paper presents a comparative study of two different methods, which are based on fusion and polar transformation of visual and thermal images. Here, investigation is done to handle the challenges of face recognition, which include pose variations, changes in facial expression, partial occlusions, variations in illumination, rotation through different angles, change in scale etc. To overcome these obstacles we have implemented and thoroughly examined two different fusion techniques through rigorous experimentation. In the first method log-polar transformation is applied to the fused images obtained after fusion of visual and thermal images whereas in second method fusion is applied on log-polar transformed individual visual and thermal images. After this step, which is thus obtained in one form or another, Principal Component Analysis (PCA) is applied to reduce dimension of the fused images. Log-polar transformed images are capable of handling complicacies introduced by scaling and rotation. The main objective of employing fusion is to produce a fused image that provides more detailed and reliable information, which is capable to overcome the drawbacks present in the individual visual and thermal face images. Finally, those reduced fused images are classified using a multilayer perceptron neural network. The database used for the experiments conducted here is Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database benchmark thermal and visual face images. The second method has shown better performance, which is 95.71% (maximum) and on an average 93.81% as correct recognition rate.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129313661","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: 7

Comparing dynamic PSO algorithms for adapting classifier ensembles in video-based face recognition 基于视频的人脸识别中自适应分类器集成的动态粒子群算法比较

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949226

J. Connolly, Eric Granger, R. Sabourin

{"title":"Comparing dynamic PSO algorithms for adapting classifier ensembles in video-based face recognition","authors":"J. Connolly, Eric Granger, R. Sabourin","doi":"10.1109/CIBIM.2011.5949226","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949226","url":null,"abstract":"Biometric models are typically designed a priori using limited number of samples acquired from complex environments that change in time during operations. Therefore, these models are often poor representatives of the biometric trait to be recognized. To circumvent this problem, ensemble of classifiers can be used to integrate solutions obtained from multiple diverse classifiers. In this paper, two dynamic particle swarm optimization (DPSO) algorithms are compared for the evolution of classifier ensembles during supervised incremental learning of newly-acquired data samples in video-based face recognition. Using the properties of these population-based optimization algorithms, an incremental DPSO learning strategy for adaptive classification systems (ACSs) is employed to evolve a pool of fuzzy ARTMAP classifiers while an heterogeneous ensemble is selected through a greedy search process that seeks to maximize both performance and diversity. The performance of dynamic niching PSO (DNPSO) and speciation PSO (SPSO) algorithms is assessed in terms of classification rate, resource requirements and diversity for different incremental learning scenarios of new data blocks extracted from real-world video streams. Simulation results indicate that both DPSO algorithms can efficiently create accurate ensembles while reducing computational complexity. In addition, directly selecting representative subswarm particles to form diversified classifier ensembles significantly reduces the computational complexity.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129274607","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

Multi-order biometric score analysis framework and its application to designing and evaluating biometric systems for access and border control 多阶生物特征评分分析框架及其在出入境生物特征系统设计与评价中的应用

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949204

D. Gorodnichy

{"title":"Multi-order biometric score analysis framework and its application to designing and evaluating biometric systems for access and border control","authors":"D. Gorodnichy","doi":"10.1109/CIBIM.2011.5949204","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949204","url":null,"abstract":"Traditionally, automated access and border control biometric systems are thought of and designed as verification 1-to-1 systems, where a single comparison between a probe and the claimed identity is examined to allow or disallow the entry to a person; and as such they have been evaluated to date - by using the error tradeoff statistics, which counts how many times a person was falsely accepted or rejected. Such a design however may soon become obsolete due to the recent shift towards applying biometrics to free-flow surveillance-like environments and also in the light of recent findings showing that performance of many verification systems can be improved through the use of several 1-to-N scores, instead of relying on a single 1-to-1 score only. As the framework for designing biometric-enabled access and border control systems changes, so has to change the methodology for the evaluation of such systems. This paper addresses this problem by establishing the multi-order biometric score analysis framework. The framework incorporates latest innovations and recommendations related to the comprehensive evaluation of biometric systems, including subject-based analysis, calibrated score analysis, and two new performance metrics: threshold-validated recognition ranking and non-confident decisions due to multiple threshold-validated scores. The framework is implemented in the Comprehensive Biometrics Evaluation Toolkit (C-BET) and has been applied for the evaluation of several biometric modalities, in particular, those that are frequently contemplated for the use in unconstrained access-border control applications, such as face, voice and iris. The results of the iris modality evaluation are presented in this paper.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117180398","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: 15

Exploring the upper bound performance limit of iris biometrics using score calibration and fusion 利用分数校准和融合技术探索虹膜生物识别的性能上限

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949213

D. Gorodnichy, Elan Dubrofsky, Richard Hoshino, Wael Khreich, Eric Granger, R. Sabourin

{"title":"Exploring the upper bound performance limit of iris biometrics using score calibration and fusion","authors":"D. Gorodnichy, Elan Dubrofsky, Richard Hoshino, Wael Khreich, Eric Granger, R. Sabourin","doi":"10.1109/CIBIM.2011.5949213","DOIUrl":"https://doi.org/10.1109/CIBIM.2011.5949213","url":null,"abstract":"Researchers now acknowledge that the ultimate goal for biometric technologies to be error-free may never be achieved for any biometric modality. The key interest therefore for any biometric modality is to know its current performance limits. For the iris modality, which is intensively used for trusted traveller programs in many countries, the question of the iris recognition limitations is of particular importance, as it affects security risk mitigation strategies employed by the programs. In this paper, we provide the answer to this question, based on the recent large-scale evaluations of state-of-the-art iris biometrics systems conducted by the National Institute of Standards and Technology (NIST) and the Canada Border Services Agency (CBSA) and two performance-improving post-processing methods developed by the CBSA and its academic partners: one based on score recalibration and the other based on fusion of decisions from multiple systems. Particular emphasis of the paper is on the description of datasets used in iris evaluations and the presentation of the new large-scale iris dataset created for the purpose at the CBSA. The importance of proper evaluation metrics and methodologies used in iris evaluations, including the subject-based analysis, is discussed.","PeriodicalId":396721,"journal":{"name":"2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123237819","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

Self adaptive systems: An experimental analysis of the performance over time 自适应系统:性能随时间变化的实验分析

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949222

A. Rattani, G. Marcialis, F. Roli

引用次数: 28

On the fusion of possibilistic and probabilistic information in biometric decision-making 生物识别决策中可能性与概率信息的融合

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949205

R. Yager

引用次数: 1

Feature selection for improved automatic gender classification 改进的性别自动分类特征选择

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM) Pub Date : 2011-04-11 DOI: 10.1109/CIBIM.2011.5949221

Yaw Chang, Yishi Wang, K. Ricanek, Cuixian Chen

引用次数: 8