Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449673
Rudolf Haraksim, Alexandre Anthonioz, C. Champod, M. Olsen, John Ellingsgaard, C. Busch
The purpose of this paper is to present a comparative study on the performance of altered fingerprint detection algorithms. Different algorithms from different institutions have been evaluated on two different datasets. Both datasets feature real alterations on fingers and the ground truth regarding the alteration is known a priori, as, in some cases, corresponding pre-altered fingerprints were also available. The performance obtained on both datasets produced by either reference state-of-the-art or custom-built algorithms is higher than the reported 10% EER from previous studies [1].
{"title":"Altered fingerprint detection – algorithm performance evaluation","authors":"Rudolf Haraksim, Alexandre Anthonioz, C. Champod, M. Olsen, John Ellingsgaard, C. Busch","doi":"10.1109/IWBF.2016.7449673","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449673","url":null,"abstract":"The purpose of this paper is to present a comparative study on the performance of altered fingerprint detection algorithms. Different algorithms from different institutions have been evaluated on two different datasets. Both datasets feature real alterations on fingers and the ground truth regarding the alteration is known a priori, as, in some cases, corresponding pre-altered fingerprints were also available. The performance obtained on both datasets produced by either reference state-of-the-art or custom-built algorithms is higher than the reported 10% EER from previous studies [1].","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133221961","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}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449688
F. Alonso-Fernandez, J. Bigün
Periocular biometrics has been established as an independent modality due to concerns on the performance of iris or face systems in uncontrolled conditions. Periocular refers to the facial region in the eye vicinity, including eyelids, lashes and eyebrows. It is available over a wide range of acquisition distances, representing a trade-off between the whole face (which can be occluded at close distances) and the iris texture (which do not have enough resolution at long distances). Since the periocular region appears in face or iris images, it can be used also in conjunction with these modalities. Features extracted from the periocular region have been also used successfully for gender classification and ethnicity classification, and to study the impact of gender transformation or plastic surgery in the recognition performance. This paper presents a review of the state of the art in periocular biometric research, providing an insight of the most relevant issues and giving a thorough coverage of the existing literature. Future research trends are also briefly discussed.
{"title":"Periocular biometrics: databases, algorithms and directions","authors":"F. Alonso-Fernandez, J. Bigün","doi":"10.1109/IWBF.2016.7449688","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449688","url":null,"abstract":"Periocular biometrics has been established as an independent modality due to concerns on the performance of iris or face systems in uncontrolled conditions. Periocular refers to the facial region in the eye vicinity, including eyelids, lashes and eyebrows. It is available over a wide range of acquisition distances, representing a trade-off between the whole face (which can be occluded at close distances) and the iris texture (which do not have enough resolution at long distances). Since the periocular region appears in face or iris images, it can be used also in conjunction with these modalities. Features extracted from the periocular region have been also used successfully for gender classification and ethnicity classification, and to study the impact of gender transformation or plastic surgery in the recognition performance. This paper presents a review of the state of the art in periocular biometric research, providing an insight of the most relevant issues and giving a thorough coverage of the existing literature. Future research trends are also briefly discussed.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114609295","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}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449676
Javier Galbally, M. Gomez-Barrero
To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured physical synthetic sample, is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. The whole biometric community, including researchers, developers, standardizing bodies and vendors, has thrown itself into the very challenging task of proposing and developing efficient protection methods against this threat, known as spoofing. The goal of this paper is to provide a comprehensive and structured overview on the work that has been carried out over the last decade in the field of iris anti-spoofing. In brief, the paper has been thought as a tool to provide biometric researchers an overall picture of the current panorama in the mentioned area following a systematic approach.
{"title":"A review of iris anti-spoofing","authors":"Javier Galbally, M. Gomez-Barrero","doi":"10.1109/IWBF.2016.7449676","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449676","url":null,"abstract":"To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured physical synthetic sample, is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. The whole biometric community, including researchers, developers, standardizing bodies and vendors, has thrown itself into the very challenging task of proposing and developing efficient protection methods against this threat, known as spoofing. The goal of this paper is to provide a comprehensive and structured overview on the work that has been carried out over the last decade in the field of iris anti-spoofing. In brief, the paper has been thought as a tool to provide biometric researchers an overall picture of the current panorama in the mentioned area following a systematic approach.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125097879","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}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449691
L. Mezai, F. Hachouf
In this paper, an adaptive multimodal biometric fusion algorithm is proposed. It is based on belief functions and Particle Swarm Optimization (PSO). The fusion is performed at the score level using belief functions such as Dempster Shafer, Yager, Proportional Conflict Redistribution and Dezert-Smarandache hybrid rules. A hybrid PSO is employed to select the best belief function and estimate its parameters. Several experiments have been conducted on BANCA dataset and a comparison between the well established methods has been performed. The preliminary results provide adequate motivation towards future research in the application of optimization techniques in the belief functions.
{"title":"Adaptive multimodal biometric fusion algorithm using particle swarm optimization and belief functions","authors":"L. Mezai, F. Hachouf","doi":"10.1109/IWBF.2016.7449691","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449691","url":null,"abstract":"In this paper, an adaptive multimodal biometric fusion algorithm is proposed. It is based on belief functions and Particle Swarm Optimization (PSO). The fusion is performed at the score level using belief functions such as Dempster Shafer, Yager, Proportional Conflict Redistribution and Dezert-Smarandache hybrid rules. A hybrid PSO is employed to select the best belief function and estimate its parameters. Several experiments have been conducted on BANCA dataset and a comparison between the well established methods has been performed. The preliminary results provide adequate motivation towards future research in the application of optimization techniques in the belief functions.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129603213","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}
Pub Date : 2016-03-01DOI: 10.1109/IWBF.2016.7449695
M. Hildebrandt, J. Dittmann
Based on the existing StirTraceV2.0 framework including 13 single artifact simulations for benchmarking artificial sweat printed fingerprint detection to identify crime scene forgeries, we propose and investigate the tilting of the sample as a further acquisition condition for Confocal Laser Scanning Microscopes (CLSM). We study Benford's law, edge- and circle-based feature detection spaces on intensity (int) and on topography (topo) image data separately. Tilting artifact reduction pre-processing is proposed as Best Fit Plane Subtraction (subp, using the known least squares method) to improve detection results. An evaluation with seven different tilting parameters with and without the proposed Best Fit Plane Subtraction is performed and discussed. To support benchmarking, StirTrace is enhanced with so-called StirTrace Evaluation Modes to perform different benchmarking tasks, such as the "printedFP" mode offering 10 edge-based features and 67 circle-based as well 9 Benford's law based detection features. The experimental data consists of 3000 printed and 3000 real fingerprint samples acquired by a CLSM. Based on different tilting parameters 21000 samples are created using StirTrace. We observe that tilting has a higher impact on the detection of forgeries using intensity data and that the proposed corrections with the Best Fit Plane Subtraction can be recommended to stabilize the detection performance. Furthermore, we analyze the impact of this pre-processing on the distribution of the most significant digits within noise data relevant for Benford's law based detection feature space.
{"title":"StirTraceV3.0 and printed fingerprint detection: Simulation of acquisition condition tilting and its impact to latent fingerprint detection feature spaces for crime scene forgeries","authors":"M. Hildebrandt, J. Dittmann","doi":"10.1109/IWBF.2016.7449695","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449695","url":null,"abstract":"Based on the existing StirTraceV2.0 framework including 13 single artifact simulations for benchmarking artificial sweat printed fingerprint detection to identify crime scene forgeries, we propose and investigate the tilting of the sample as a further acquisition condition for Confocal Laser Scanning Microscopes (CLSM). We study Benford's law, edge- and circle-based feature detection spaces on intensity (int) and on topography (topo) image data separately. Tilting artifact reduction pre-processing is proposed as Best Fit Plane Subtraction (subp, using the known least squares method) to improve detection results. An evaluation with seven different tilting parameters with and without the proposed Best Fit Plane Subtraction is performed and discussed. To support benchmarking, StirTrace is enhanced with so-called StirTrace Evaluation Modes to perform different benchmarking tasks, such as the \"printedFP\" mode offering 10 edge-based features and 67 circle-based as well 9 Benford's law based detection features. The experimental data consists of 3000 printed and 3000 real fingerprint samples acquired by a CLSM. Based on different tilting parameters 21000 samples are created using StirTrace. We observe that tilting has a higher impact on the detection of forgeries using intensity data and that the proposed corrections with the Best Fit Plane Subtraction can be recommended to stabilize the detection performance. Furthermore, we analyze the impact of this pre-processing on the distribution of the most significant digits within noise data relevant for Benford's law based detection feature space.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126558034","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}
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