Pub Date : 2015-05-19DOI: 10.1109/ICB.2015.7139062
Sunpreet S. Arora, Kai Cao, Anil K. Jain, Gregoire Michaud
Automatic matching of poor quality latent fingerprints to rolled/slap fingerprints using an Automated Fingerprint Identification System (AFIS) is still far from satisfactory. Therefore, it is a common practice to have a latent examiner mark features on a latent for improving the hit rate of the AFIS. We propose a synergistic crowd powered latent identification framework where multiple latent examiners and the AFIS work in conjunction with each other to boost the identification accuracy of the AFIS. Given a latent, the candidate list output by the AFIS is used to determine the likelihood that a hit at rank-1 was found. A latent for which this likelihood is low is crowdsourced to a pool of latent examiners for feature markup. The manual markups are then input to the AFIS to increase the likelihood of making a hit in the reference database. Experimental results show that the fusion of an AFIS with examiner markups improves the rank-1 identification accuracy of the AFIS by 7.75% (using six markups) on the 500 ppi NIST SD27, 11.37% (using two markups) on the 1000 ppi ELFT-EFS public challenge database, and by 2.5% (using a single markup) on the 1000 ppi RS&A database against 250,000 rolled prints in the reference database.
{"title":"Crowd powered latent Fingerprint Identification: Fusing AFIS with examiner markups","authors":"Sunpreet S. Arora, Kai Cao, Anil K. Jain, Gregoire Michaud","doi":"10.1109/ICB.2015.7139062","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139062","url":null,"abstract":"Automatic matching of poor quality latent fingerprints to rolled/slap fingerprints using an Automated Fingerprint Identification System (AFIS) is still far from satisfactory. Therefore, it is a common practice to have a latent examiner mark features on a latent for improving the hit rate of the AFIS. We propose a synergistic crowd powered latent identification framework where multiple latent examiners and the AFIS work in conjunction with each other to boost the identification accuracy of the AFIS. Given a latent, the candidate list output by the AFIS is used to determine the likelihood that a hit at rank-1 was found. A latent for which this likelihood is low is crowdsourced to a pool of latent examiners for feature markup. The manual markups are then input to the AFIS to increase the likelihood of making a hit in the reference database. Experimental results show that the fusion of an AFIS with examiner markups improves the rank-1 identification accuracy of the AFIS by 7.75% (using six markups) on the 500 ppi NIST SD27, 11.37% (using two markups) on the 1000 ppi ELFT-EFS public challenge database, and by 2.5% (using a single markup) on the 1000 ppi RS&A database against 250,000 rolled prints in the reference database.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132734425","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 : 2015-05-19DOI: 10.1109/ICB.2015.7139047
Rubén Tolosana, R. Vera-Rodríguez, J. Ortega-Garcia, Julian Fierrez
Due to the technological evolution and the increasing popularity of smartphones, people can access an application with many different devices. This device interoperability is a very challenging problem for biometrics. In this paper we focus on inter-operability device compensation for on-line signature verification. The proposed approach is based on two main stages. The first one is a preprocessing stage where data acquired from different devices are processed in order to normalize the signals in similar ranges. The second one is based on a feature selection of time functions taking into account the inter-operability device comparisons in order to select features which are robust in these conditions. The experimental work has been carried out with Biosecure database using a Wacom tablet (DS2) and a PDA tablet (DS3), and the system developed is based on dynamic time warping (DTW) elastic measure over the selected time functions. The performance of the proposed system is very similar compared to an ideal system. Also, the proposed approach provides average relative improvements for the cases of inter-operability comparisons of 26.5% for random forgeries and, around 14.2% for the case of skilled forgeries comparing the results with the case of having a system specifically tuned for each device, proving the robustness of the proposed approach. These results open the door for future works using devices as smartphones or tablets, commonly used nowadays.
{"title":"Optimal feature selection and inter-operability compensation for on-line biometric signature authentication","authors":"Rubén Tolosana, R. Vera-Rodríguez, J. Ortega-Garcia, Julian Fierrez","doi":"10.1109/ICB.2015.7139047","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139047","url":null,"abstract":"Due to the technological evolution and the increasing popularity of smartphones, people can access an application with many different devices. This device interoperability is a very challenging problem for biometrics. In this paper we focus on inter-operability device compensation for on-line signature verification. The proposed approach is based on two main stages. The first one is a preprocessing stage where data acquired from different devices are processed in order to normalize the signals in similar ranges. The second one is based on a feature selection of time functions taking into account the inter-operability device comparisons in order to select features which are robust in these conditions. The experimental work has been carried out with Biosecure database using a Wacom tablet (DS2) and a PDA tablet (DS3), and the system developed is based on dynamic time warping (DTW) elastic measure over the selected time functions. The performance of the proposed system is very similar compared to an ideal system. Also, the proposed approach provides average relative improvements for the cases of inter-operability comparisons of 26.5% for random forgeries and, around 14.2% for the case of skilled forgeries comparing the results with the case of having a system specifically tuned for each device, proving the robustness of the proposed approach. These results open the door for future works using devices as smartphones or tablets, commonly used nowadays.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130140864","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 : 2015-05-19DOI: 10.1109/ICB.2015.7139040
Thomas Bergmüller, Eleftherios Christopoulos, Martin Schnoell, A. Uhl
Rating a compression algorithm's performance is usually done in experimental studies, where researchers have frequently used JPEG pre-compressed data. It is not clear yet, whether results of such compression experiments are reliable if conducted from pre-compressed data. To investigate this issue, we study the impact of using pre-compressed data on iris segmentation and evaluate the relation between iris segmentation performance and general quality metrics. Furthermore we propose a method to overcome potential problems in case using pre-compressed data sets cannot be avoided, e.g. for reasons of ground-truth availability.
{"title":"Recompression effects in iris segmentation","authors":"Thomas Bergmüller, Eleftherios Christopoulos, Martin Schnoell, A. Uhl","doi":"10.1109/ICB.2015.7139040","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139040","url":null,"abstract":"Rating a compression algorithm's performance is usually done in experimental studies, where researchers have frequently used JPEG pre-compressed data. It is not clear yet, whether results of such compression experiments are reliable if conducted from pre-compressed data. To investigate this issue, we study the impact of using pre-compressed data on iris segmentation and evaluate the relation between iris segmentation performance and general quality metrics. Furthermore we propose a method to overcome potential problems in case using pre-compressed data sets cannot be avoided, e.g. for reasons of ground-truth availability.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"74 5-6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131791660","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 : 2015-05-19DOI: 10.1109/ICB.2015.7139049
Akanksha Joshi, A. Gangwar
In this paper, we introduce new methods to encode color local texture features for enhanced face representation. In particular, we first propose a novel descriptor; color local phase quantization (CLPQ), which incorporates (channel-wise) unichrome and (cross channel) opponent features in frequency domain. Furthermore, we extend the CLPQ descriptor to multiple scales i.e. multiscale color LPQ (MS-CLPQ), which exploits the complementary information in different scales. In addition, we extend the multispectral LBP to multiple scales and propose multiscale color LBP (MS-CLBP), which provides illumination invariance and extracts features in spatial domain. To formulate the proposed color local texture descriptors, the unichrome and opponent features are combined using image-level fusion strategy and final representation of the descriptors is obtained using concatenation of regional histograms. To reduce high dimensionality of features, we applied Direct LDA, which also enhances the discrimination ability of the descriptors. The experimental analysis illustrates that proposed MS-CLPQ approach significantly outperforms other descriptor based approaches for face recognition (FR) and score level fusion of MS-CLPQ and MS-CLBP further improves the FR performance and robustness. The validity of the proposed approaches is ascertained by providing comprehensive comparisons on three challenging face databases; FRGC 2.0, GTDB and PUT.
{"title":"Color local phase quantization (CLPQ)- A new face representation approach using color texture cues","authors":"Akanksha Joshi, A. Gangwar","doi":"10.1109/ICB.2015.7139049","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139049","url":null,"abstract":"In this paper, we introduce new methods to encode color local texture features for enhanced face representation. In particular, we first propose a novel descriptor; color local phase quantization (CLPQ), which incorporates (channel-wise) unichrome and (cross channel) opponent features in frequency domain. Furthermore, we extend the CLPQ descriptor to multiple scales i.e. multiscale color LPQ (MS-CLPQ), which exploits the complementary information in different scales. In addition, we extend the multispectral LBP to multiple scales and propose multiscale color LBP (MS-CLBP), which provides illumination invariance and extracts features in spatial domain. To formulate the proposed color local texture descriptors, the unichrome and opponent features are combined using image-level fusion strategy and final representation of the descriptors is obtained using concatenation of regional histograms. To reduce high dimensionality of features, we applied Direct LDA, which also enhances the discrimination ability of the descriptors. The experimental analysis illustrates that proposed MS-CLPQ approach significantly outperforms other descriptor based approaches for face recognition (FR) and score level fusion of MS-CLPQ and MS-CLBP further improves the FR performance and robustness. The validity of the proposed approaches is ascertained by providing comprehensive comparisons on three challenging face databases; FRGC 2.0, GTDB and PUT.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131230893","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}
Research in face recognition under constrained environment has achieved an acceptable level of performance. However, there is a significant scope for improving face recognition capabilities in unconstrained environment including surveillance videos. Such videos are likely to record multiple people within the field of view. Face recognition in such a setting poses a set of challenges including unreliable face detection, multiple subjects performing different actions, low resolution, and sensor interoperability. In general, existing video face databases contain one subject in a video sequence. However, real world video sequences are more challenging and generally contain more than one person in a video. Therefore, in this paper, we provide an annotated crowd video face (ACVF-2014) database, along with face landmark information to encourage research in this important problem. The ACVF-2014 dataset contains 201 videos of 133 subjects where each video contains multiple subjects. We provide two distinct use-case scenarios, define their experimental protocols, and report baseline verification results using OpenBR and FaceVACS. The results show that both the baseline results do not yield more than 0.16 genuine accept rate @ 0.01 false accept rate. A software package is also developed to help researchers evaluate their systems using the defined protocols.
{"title":"Annotated crowd video face database","authors":"Tejas I. Dhamecha, Priyanka Verma, Mahek Shah, Richa Singh, Mayank Vatsa","doi":"10.1109/ICB.2015.7139083","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139083","url":null,"abstract":"Research in face recognition under constrained environment has achieved an acceptable level of performance. However, there is a significant scope for improving face recognition capabilities in unconstrained environment including surveillance videos. Such videos are likely to record multiple people within the field of view. Face recognition in such a setting poses a set of challenges including unreliable face detection, multiple subjects performing different actions, low resolution, and sensor interoperability. In general, existing video face databases contain one subject in a video sequence. However, real world video sequences are more challenging and generally contain more than one person in a video. Therefore, in this paper, we provide an annotated crowd video face (ACVF-2014) database, along with face landmark information to encourage research in this important problem. The ACVF-2014 dataset contains 201 videos of 133 subjects where each video contains multiple subjects. We provide two distinct use-case scenarios, define their experimental protocols, and report baseline verification results using OpenBR and FaceVACS. The results show that both the baseline results do not yield more than 0.16 genuine accept rate @ 0.01 false accept rate. A software package is also developed to help researchers evaluate their systems using the defined protocols.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133818090","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 : 2015-05-19DOI: 10.1109/ICB.2015.7139056
Pedro Tome, S. Marcel
The vulnerability of palm vein recognition to spoofing attacks is studied in this paper. A collection of spoofing palm vein images has been created from real palm vein samples. Palm vein images are printed using a commercial printer and then, presented at a contactless palm vein sensor. Experiments are carried out using an extensible framework, which allows fair and reproducible benchmarks. Results are presented comparing two automatic segmentations. Experimental results lead to a spoofing false accept rate of 65%, thus showing that palm vein biometrics is vulnerable to spoofing attacks, pointing out the importance to investigate countermeasures against this type of fraudulent actions. A study based on the number of the enrolment samples is also reported, demonstrating a relationship between the number of enrolment samples and the vulnerability of the system to spoofing.
{"title":"On the vulnerability of palm vein recognition to spoofing attacks","authors":"Pedro Tome, S. Marcel","doi":"10.1109/ICB.2015.7139056","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139056","url":null,"abstract":"The vulnerability of palm vein recognition to spoofing attacks is studied in this paper. A collection of spoofing palm vein images has been created from real palm vein samples. Palm vein images are printed using a commercial printer and then, presented at a contactless palm vein sensor. Experiments are carried out using an extensible framework, which allows fair and reproducible benchmarks. Results are presented comparing two automatic segmentations. Experimental results lead to a spoofing false accept rate of 65%, thus showing that palm vein biometrics is vulnerable to spoofing attacks, pointing out the importance to investigate countermeasures against this type of fraudulent actions. A study based on the number of the enrolment samples is also reported, demonstrating a relationship between the number of enrolment samples and the vulnerability of the system to spoofing.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115664941","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 : 2015-05-19DOI: 10.1109/ICB.2015.7139044
K. Raja, Ramachandra Raghavendra, Martin Stokkenes, C. Busch
Secure authentication for smartphones is becoming important for many applications such as financial transactions. Until today PIN and password authentication are the most commonly used methods for smartphone access control. Specifically for a PIN and limited length passwords, the level of security is low and thus can be compromised easily. In this work, we propose a multi-modal biometric system, which uses face, periocular and iris biometric characteristics for authentication. The proposed system is tested on two different devices - Samsung Galaxy S5 smartphone and Samsung Galaxy Note 10.1 tablet. An extensive set of experiments conducted using the proposed system shows the applicability for secure authentication scenarios. The proposed system is tested using uni-modal and multi-modal approach. An Equal Error Rate (EER) of 0.68% is obtained from the experiments validating the robust performance of the proposed system.
{"title":"Multi-modal authentication system for smartphones using face, iris and periocular","authors":"K. Raja, Ramachandra Raghavendra, Martin Stokkenes, C. Busch","doi":"10.1109/ICB.2015.7139044","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139044","url":null,"abstract":"Secure authentication for smartphones is becoming important for many applications such as financial transactions. Until today PIN and password authentication are the most commonly used methods for smartphone access control. Specifically for a PIN and limited length passwords, the level of security is low and thus can be compromised easily. In this work, we propose a multi-modal biometric system, which uses face, periocular and iris biometric characteristics for authentication. The proposed system is tested on two different devices - Samsung Galaxy S5 smartphone and Samsung Galaxy Note 10.1 tablet. An extensive set of experiments conducted using the proposed system shows the applicability for secure authentication scenarios. The proposed system is tested using uni-modal and multi-modal approach. An Equal Error Rate (EER) of 0.68% is obtained from the experiments validating the robust performance of the proposed system.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114993553","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 : 2015-05-19DOI: 10.1109/ICB.2015.7139064
Shuiwang Li, Yi Alice Wang, Qijun Zhao, Yi Zhang
Fingerprint minutiae distribution plays a critical role in studies such as fingerprint individuality for strengthening the scientific validity of fingerprint evidence and generating synthetic fingerprints for large-scale system evaluations. Fingerprint minutiae are not uniformly distributed as once assumed. Spatial inhomogeneity has been found in minutiae distribution, yet it is not clear what underlies the pattern and affects the random process. In this paper, we quantitatively study the spatial inhomogeneity of minutiae distribution with respect to the level-1 features of singular points and ridge orientation field. We propose a minutiae intensity function to measure the spatial inhomogeneity and a kernel regression model to characterize the relationship between minutiae intensity and the level-1 features. Our statistical experiments on benchmark fingerprint databases show that: 1) the examined level-1 features partially explain regular variation of minutiae spatial distribution; 2) there remain significant fraction of variations unexplained, suggesting additional propositions. These results provide better understanding of the experiential probability of a random correspondence for fingerprint minutiae distribution modelling.
{"title":"On the spatial inhomogeneity of fingerprint minutiae: A regression approach","authors":"Shuiwang Li, Yi Alice Wang, Qijun Zhao, Yi Zhang","doi":"10.1109/ICB.2015.7139064","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139064","url":null,"abstract":"Fingerprint minutiae distribution plays a critical role in studies such as fingerprint individuality for strengthening the scientific validity of fingerprint evidence and generating synthetic fingerprints for large-scale system evaluations. Fingerprint minutiae are not uniformly distributed as once assumed. Spatial inhomogeneity has been found in minutiae distribution, yet it is not clear what underlies the pattern and affects the random process. In this paper, we quantitatively study the spatial inhomogeneity of minutiae distribution with respect to the level-1 features of singular points and ridge orientation field. We propose a minutiae intensity function to measure the spatial inhomogeneity and a kernel regression model to characterize the relationship between minutiae intensity and the level-1 features. Our statistical experiments on benchmark fingerprint databases show that: 1) the examined level-1 features partially explain regular variation of minutiae spatial distribution; 2) there remain significant fraction of variations unexplained, suggesting additional propositions. These results provide better understanding of the experiential probability of a random correspondence for fingerprint minutiae distribution modelling.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129740889","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 : 2015-05-19DOI: 10.1109/ICB.2015.7139080
Ran Xian, Liao Ni, Wenxin Li
Finger vein recognition is a newly developed and promising biometrics technology. To facilitate evaluation in this area and study state-of-the-art performance of the finger vein recognition algorithms, we organized The ICB-2015 Competition on Finger Vein Recognition (ICFVR2015). This competition is held on a general recognition algorithm evaluation platform called RATE, with 3 data sets collected from volunteers and actual usage. 7 algorithms were finally submitted, with the best EER achieving 0.375%. This paper will first introduce the organization of the competition and RATE, then describe data sets and test protocols, and finally present results of the competition.
{"title":"The ICB-2015 Competition on Finger Vein Recognition","authors":"Ran Xian, Liao Ni, Wenxin Li","doi":"10.1109/ICB.2015.7139080","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139080","url":null,"abstract":"Finger vein recognition is a newly developed and promising biometrics technology. To facilitate evaluation in this area and study state-of-the-art performance of the finger vein recognition algorithms, we organized The ICB-2015 Competition on Finger Vein Recognition (ICFVR2015). This competition is held on a general recognition algorithm evaluation platform called RATE, with 3 data sets collected from volunteers and actual usage. 7 algorithms were finally submitted, with the best EER achieving 0.375%. This paper will first introduce the organization of the competition and RATE, then describe data sets and test protocols, and finally present results of the competition.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122754899","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 : 2015-05-19DOI: 10.1109/ICB.2015.7139067
Pedro Tome, Ramachandra Raghavendra, C. Busch, Santosh Tirunagari, N. Poh, B. H. Shekar, Diego Gragnaniello, Carlo Sansone, L. Verdoliva, S. Marcel
The vulnerability of finger vein recognition to spoofing attacks has emerged as a crucial security problem in the recent years mainly due to the high security applications where biometric technology is used. Recent works shown that finger vein biometrics is vulnerable to spoofing attacks, pointing out the importance to investigate counter-measures against this type of fraudulent actions. The goal of the 1st Competition on Counter Measures to Finger Vein Spoofing Attacks is to challenge researchers to create counter-measures that can detect printed attacks effectively. The submitted approaches are evaluated on the Spoofing-Attack Finger Vein Database and the achieved results are presented in this paper.
{"title":"The 1st Competition on Counter Measures to Finger Vein Spoofing Attacks","authors":"Pedro Tome, Ramachandra Raghavendra, C. Busch, Santosh Tirunagari, N. Poh, B. H. Shekar, Diego Gragnaniello, Carlo Sansone, L. Verdoliva, S. Marcel","doi":"10.1109/ICB.2015.7139067","DOIUrl":"https://doi.org/10.1109/ICB.2015.7139067","url":null,"abstract":"The vulnerability of finger vein recognition to spoofing attacks has emerged as a crucial security problem in the recent years mainly due to the high security applications where biometric technology is used. Recent works shown that finger vein biometrics is vulnerable to spoofing attacks, pointing out the importance to investigate counter-measures against this type of fraudulent actions. The goal of the 1st Competition on Counter Measures to Finger Vein Spoofing Attacks is to challenge researchers to create counter-measures that can detect printed attacks effectively. The submitted approaches are evaluated on the Spoofing-Attack Finger Vein Database and the achieved results are presented in this paper.","PeriodicalId":237372,"journal":{"name":"2015 International Conference on Biometrics (ICB)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123980556","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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