Pub Date : 2011-10-11DOI: 10.1109/IJCB.2011.6117513
D. Reid, M. Nixon
Soft biometrics is a new form of biometric identification which utilizes labeled physical or behavioral traits. Although these traits intuitively have less discriminatory capability than mensurate approaches, they offer several advantages over traditional biometric techniques. Soft biometric traits can be typically described as labels and measurements which can be understood by people, allowing retrieval and recognition based solely on human descriptions. Although being a key component of eyewitness evidence, conventional human descriptions can be considered to be unreliable. A novel method of obtaining human descriptions will be introduced which utilizes visual comparisons between subjects. The Elo rating system is used to infer relative measurements of subjects' traits based on the comparative human descriptions. This innovative approach to obtaining human descriptions has been shown to counter many problems associated with categorical (absolute) labels. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate retrieval of subjects in video data and show that elapsed time can have little effect on comparative descriptions.
{"title":"Using comparative human descriptions for soft biometrics","authors":"D. Reid, M. Nixon","doi":"10.1109/IJCB.2011.6117513","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117513","url":null,"abstract":"Soft biometrics is a new form of biometric identification which utilizes labeled physical or behavioral traits. Although these traits intuitively have less discriminatory capability than mensurate approaches, they offer several advantages over traditional biometric techniques. Soft biometric traits can be typically described as labels and measurements which can be understood by people, allowing retrieval and recognition based solely on human descriptions. Although being a key component of eyewitness evidence, conventional human descriptions can be considered to be unreliable. A novel method of obtaining human descriptions will be introduced which utilizes visual comparisons between subjects. The Elo rating system is used to infer relative measurements of subjects' traits based on the comparative human descriptions. This innovative approach to obtaining human descriptions has been shown to counter many problems associated with categorical (absolute) labels. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate retrieval of subjects in video data and show that elapsed time can have little effect on comparative descriptions.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127038949","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117549
Daniel Hartung, M. Olsen, Hai-yun Xu, C. Busch
Similar to biometric fingerprint recognition, characteristic minutiae points - here end- and branch points - can be extracted from skeletonized veins to distinguish individuals. An approach to extract those vein minutiae and to transform them into a fixed-length, translation and scale invariant representation where rotations can be easily compensated is presented in this paper. The proposed solution based on spectral minutiae is evaluated against other comparison strategies on three different datasets of wrist and palm vein samples. It shows a competitive biometric performance while producing features that are compatible with state-of-the-art template protection systems.
与生物指纹识别类似，可以从骨骼化的静脉中提取特征细枝末节点(end- and - branch points)来区分个体。本文提出了一种提取这些静脉细部的方法，并将其转化为可轻松补偿旋转的定长、平移和尺度不变的表示。在三个不同的手腕和手掌静脉样本数据集上，对基于频谱细节的方法与其他比较策略进行了评估。它显示了具有竞争力的生物识别性能，同时产生与最先进的模板保护系统兼容的功能。
{"title":"Spectral minutiae for vein pattern recognition","authors":"Daniel Hartung, M. Olsen, Hai-yun Xu, C. Busch","doi":"10.1109/IJCB.2011.6117549","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117549","url":null,"abstract":"Similar to biometric fingerprint recognition, characteristic minutiae points - here end- and branch points - can be extracted from skeletonized veins to distinguish individuals. An approach to extract those vein minutiae and to transform them into a fixed-length, translation and scale invariant representation where rotations can be easily compensated is presented in this paper. The proposed solution based on spectral minutiae is evaluated against other comparison strategies on three different datasets of wrist and palm vein samples. It shows a competitive biometric performance while producing features that are compatible with state-of-the-art template protection systems.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124904044","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117540
Rama Kovvuri, A. Namboodiri
We propose a novel approach to enhance the fingerprint image and extract features such as directional fields, minutiae and singular points reliably using a Hierarchical Markov Random Field Model. Unlike traditional fingerprint enhancement techniques, we use previously learned prior patterns from a set of clean fingerprints to restore a noisy one. We are able to recover the ridge and valley structure from degraded and noisy fingerprint images by formulating it as a hierarchical interconnected MRF that processes the information at multiple resolutions. The top layer incorporates the compatibility between an observed degraded fingerprint patch and prior training patterns in addition to ridge continuity across neighboring patches. A second layer accounts for spatial smoothness of the orientation field and its discontinuity at the singularities. Further layers could be used for incorporating higher level priors such as the class of the fingerprint. The strength of the proposed approach lies in its flexibility to model possible variations in fingerprint images as patches and from its ability to incorporate contextual information at various resolutions. Experimental results (both quantitative and qualitative) clearly demonstrate the effectiveness of this approach.
{"title":"Fingerprint enhancement using Hierarchical Markov Random Fields","authors":"Rama Kovvuri, A. Namboodiri","doi":"10.1109/IJCB.2011.6117540","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117540","url":null,"abstract":"We propose a novel approach to enhance the fingerprint image and extract features such as directional fields, minutiae and singular points reliably using a Hierarchical Markov Random Field Model. Unlike traditional fingerprint enhancement techniques, we use previously learned prior patterns from a set of clean fingerprints to restore a noisy one. We are able to recover the ridge and valley structure from degraded and noisy fingerprint images by formulating it as a hierarchical interconnected MRF that processes the information at multiple resolutions. The top layer incorporates the compatibility between an observed degraded fingerprint patch and prior training patterns in addition to ridge continuity across neighboring patches. A second layer accounts for spatial smoothness of the orientation field and its discontinuity at the singularities. Further layers could be used for incorporating higher level priors such as the class of the fingerprint. The strength of the proposed approach lies in its flexibility to model possible variations in fingerprint images as patches and from its ability to incorporate contextual information at various resolutions. Experimental results (both quantitative and qualitative) clearly demonstrate the effectiveness of this approach.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131240737","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117520
Hemank Lamba, A. Sarkar, Mayank Vatsa, Richa Singh, A. Noore
One of the major challenges of face recognition is to design a feature extractor and matcher that reduces the intraclass variations and increases the inter-class variations. The feature extraction algorithm has to be robust enough to extract similar features for a particular subject despite variations in quality, pose, illumination, expression, aging, and disguise. The problem is exacerbated when there are two individuals with lower inter-class variations, i.e., look-alikes. In such cases, the intra-class similarity is higher than the inter-class variation for these two individuals. This research explores the problem of look-alike faces and their effect on human performance and automatic face recognition algorithms. There is three fold contribution in this research: firstly, we analyze the human recognition capabilities for look-alike appearances. Secondly, we compare human recognition performance with ten existing face recognition algorithms, and finally, proposed an algorithm to improve the face verification accuracy. The analysis shows that neither humans nor automatic face recognition algorithms are efficient in recognizing look-alikes.
{"title":"Face recognition for look-alikes: A preliminary study","authors":"Hemank Lamba, A. Sarkar, Mayank Vatsa, Richa Singh, A. Noore","doi":"10.1109/IJCB.2011.6117520","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117520","url":null,"abstract":"One of the major challenges of face recognition is to design a feature extractor and matcher that reduces the intraclass variations and increases the inter-class variations. The feature extraction algorithm has to be robust enough to extract similar features for a particular subject despite variations in quality, pose, illumination, expression, aging, and disguise. The problem is exacerbated when there are two individuals with lower inter-class variations, i.e., look-alikes. In such cases, the intra-class similarity is higher than the inter-class variation for these two individuals. This research explores the problem of look-alike faces and their effect on human performance and automatic face recognition algorithms. There is three fold contribution in this research: firstly, we analyze the human recognition capabilities for look-alike appearances. Secondly, we compare human recognition performance with ten existing face recognition algorithms, and finally, proposed an algorithm to improve the face verification accuracy. The analysis shows that neither humans nor automatic face recognition algorithms are efficient in recognizing look-alikes.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130779012","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117594
Prasanna Krishnasamy, Serge J. Belongie, D. Kriegman
Many fingers wrinkle or shrivel when immersed in water. When used for biometric identification, the recognition rate for wrinkled fingers degrades. The impact of wrinkling has so far not been well-understood. In this study, we present an investigation of how the finger-skin expansion due to wrinkling impacts the quality of scanned fingerprints and characterize the qualitative changes that affect recognition. We also introduce the Wet and Wrinkled Finger (WWF) database that we will make available to other researchers. In this database of 300 fingers, 185 are visibly wrinkled after immersion; multiple images of dry and immersed fingerprints were acquired. In this paper, we present baseline recognition rates on WWF using two algorithms - a commercial fingerprint recognition algorithm and the publicly available Bozorth3 matcher. Specifically, we show a degradation in accuracy with both algorithms when comparing Dry-finger to Dry-finger verification with Dry-finger toWet-finger verification. We analyze performance on a per-finger basis and note a difference in accuracy amongst fingers, and as consequence make recommendations about which fingers to use in environments where fingers are apt to be wet. Additionally, we propose an implementation of a classifier that can decide if the incoming query is wrinkled.
{"title":"Wet fingerprint recognition: Challenges and opportunities","authors":"Prasanna Krishnasamy, Serge J. Belongie, D. Kriegman","doi":"10.1109/IJCB.2011.6117594","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117594","url":null,"abstract":"Many fingers wrinkle or shrivel when immersed in water. When used for biometric identification, the recognition rate for wrinkled fingers degrades. The impact of wrinkling has so far not been well-understood. In this study, we present an investigation of how the finger-skin expansion due to wrinkling impacts the quality of scanned fingerprints and characterize the qualitative changes that affect recognition. We also introduce the Wet and Wrinkled Finger (WWF) database that we will make available to other researchers. In this database of 300 fingers, 185 are visibly wrinkled after immersion; multiple images of dry and immersed fingerprints were acquired. In this paper, we present baseline recognition rates on WWF using two algorithms - a commercial fingerprint recognition algorithm and the publicly available Bozorth3 matcher. Specifically, we show a degradation in accuracy with both algorithms when comparing Dry-finger to Dry-finger verification with Dry-finger toWet-finger verification. We analyze performance on a per-finger basis and note a difference in accuracy amongst fingers, and as consequence make recommendations about which fingers to use in environments where fingers are apt to be wet. Additionally, we propose an implementation of a classifier that can decide if the incoming query is wrinkled.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116683351","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117512
Xi Cheng, S. Tulyakov, V. Govindaraju
In some cases, the test person might be asked to provide another authentication attempt besides the first one so that combination of the two input templates might give the system more confidence if the person is genuine or impostor. Instead of simply combining the matching scores which are associated with a single person compared to the two input templates, we investigate the use of matching scores corresponding to all enrolled persons. The dependencies between scores generated by the same input templates are accounted for the proposed combination algorithm. Such combination methods can be extended to large number of classes and input templates. Since matching scores are used, the proposed methods can also be applied on arbitrary biometric modalities. The experiments are conducted on NIST BSSR1 face and FVC2002 fingerprint datasets by using both likelihood ratio and multilayer perceptron combination methods.
{"title":"Combination of multiple samples utilizing identification model in biometric systems","authors":"Xi Cheng, S. Tulyakov, V. Govindaraju","doi":"10.1109/IJCB.2011.6117512","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117512","url":null,"abstract":"In some cases, the test person might be asked to provide another authentication attempt besides the first one so that combination of the two input templates might give the system more confidence if the person is genuine or impostor. Instead of simply combining the matching scores which are associated with a single person compared to the two input templates, we investigate the use of matching scores corresponding to all enrolled persons. The dependencies between scores generated by the same input templates are accounted for the proposed combination algorithm. Such combination methods can be extended to large number of classes and input templates. Since matching scores are used, the proposed methods can also be applied on arbitrary biometric modalities. The experiments are conducted on NIST BSSR1 face and FVC2002 fingerprint datasets by using both likelihood ratio and multilayer perceptron combination methods.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114712769","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117543
Xuebing Zhou, Arjan Kuijper, R. Veldhuis, C. Busch
Fuzzy commitment is an efficient template protection algorithm that can improve security and safeguard privacy of biometrics. Existing theoretical security analysis has proved that although privacy leakage is unavoidable, perfect security from information-theoretical points of view is possible when bits extracted from biometric features are uniformly and independently distributed. Unfortunately, this strict condition is difficult to fulfill in practice. In many applications, dependency of binary features is ignored and security is thus suspected to be highly overestimated. This paper gives a comprehensive analysis on security and privacy of fuzzy commitment regarding empirical evaluation. The criteria representing requirements in practical applications are investigated and measured quantitatively in an existing protection system for 3D face recognition. The evaluation results show that a very significant reduction of security and enlargement of privacy leakage occur due to the dependency of biometric features. This work shows that in practice, one has to explicitly measure the security and privacy instead of trusting results under non-realistic assumptions.
{"title":"Quantifying privacy and security of biometric fuzzy commitment","authors":"Xuebing Zhou, Arjan Kuijper, R. Veldhuis, C. Busch","doi":"10.1109/IJCB.2011.6117543","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117543","url":null,"abstract":"Fuzzy commitment is an efficient template protection algorithm that can improve security and safeguard privacy of biometrics. Existing theoretical security analysis has proved that although privacy leakage is unavoidable, perfect security from information-theoretical points of view is possible when bits extracted from biometric features are uniformly and independently distributed. Unfortunately, this strict condition is difficult to fulfill in practice. In many applications, dependency of binary features is ignored and security is thus suspected to be highly overestimated. This paper gives a comprehensive analysis on security and privacy of fuzzy commitment regarding empirical evaluation. The criteria representing requirements in practical applications are investigated and measured quantitatively in an existing protection system for 3D face recognition. The evaluation results show that a very significant reduction of security and enlargement of privacy leakage occur due to the dependency of biometric features. This work shows that in practice, one has to explicitly measure the security and privacy instead of trusting results under non-realistic assumptions.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"94 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126872195","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117526
Estefan Ortiz, K. Bowyer
Current iris biometric systems enroll a person based on the best eye image taken at the time of acquisition. However, recent research has shown that simply taking the best eye image and ignoring pupil dilation leads to degradations in system performance. In particular, the probability of a false non-match increases when there is a considerable variation in pupil size between the enrolled eye image and the probe eye image. Therefore, methods of enrollment that take into account pupil dilation are needed to ensure reliability of an iris biometric system. Our research examines a strategy to improve system performance by implementing a dilation-aware enrollment phase that chooses eye images based on their respective empirical dilation ratio distribution. We compare our strategy of enrollment to that of the randomly chosen eye images, which is the current enrollment procedure for most iris biometric systems. Our results show that there is a noticeable improvement over the random scenario when pupil dilation is accounted for during the enrollment phase.
{"title":"Dilation aware multi-image enrollment for iris biometrics","authors":"Estefan Ortiz, K. Bowyer","doi":"10.1109/IJCB.2011.6117526","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117526","url":null,"abstract":"Current iris biometric systems enroll a person based on the best eye image taken at the time of acquisition. However, recent research has shown that simply taking the best eye image and ignoring pupil dilation leads to degradations in system performance. In particular, the probability of a false non-match increases when there is a considerable variation in pupil size between the enrolled eye image and the probe eye image. Therefore, methods of enrollment that take into account pupil dilation are needed to ensure reliability of an iris biometric system. Our research examines a strategy to improve system performance by implementing a dilation-aware enrollment phase that chooses eye images based on their respective empirical dilation ratio distribution. We compare our strategy of enrollment to that of the randomly chosen eye images, which is the current enrollment procedure for most iris biometric systems. Our results show that there is a noticeable improvement over the random scenario when pupil dilation is accounted for during the enrollment phase.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116407060","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117489
Nathan J. Short, A. L. Abbott, M. Hsiao, E. Fox
Fingerprints continue to serve as a reliable trait for human identification. Feature-based matching techniques, such as those used by Automated Fingerprint Identification Systems (AFIS), have demonstrated remarkable success in minutiae-based matching from good quality prints with relatively large extent. As the image quality degrades and acquired fingerprint area decreases, however, the number of reliable minutiae that can be automatically detected decreases, causing match performance to suffer. This paper presents a novel approach to improving the precision of features that can be extracted from fingerprint images. This is accomplished through improved minutia localization and quality assessment routines that are inspired in part by human visual perception. Initial results have shown an improvement in minutia accuracy for 88.2% of fingerprint minutia sets after applying the proposed localization method. An increase in average quality of true minutiae was found for 98.6% of the fingerprint images when using the proposed quality assessment. The results were obtained using a database of 516 fingerprints with ground truth minutiae.
{"title":"A Bayesian approach to fingerprint minutia localization and quality assessment using adaptable templates","authors":"Nathan J. Short, A. L. Abbott, M. Hsiao, E. Fox","doi":"10.1109/IJCB.2011.6117489","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117489","url":null,"abstract":"Fingerprints continue to serve as a reliable trait for human identification. Feature-based matching techniques, such as those used by Automated Fingerprint Identification Systems (AFIS), have demonstrated remarkable success in minutiae-based matching from good quality prints with relatively large extent. As the image quality degrades and acquired fingerprint area decreases, however, the number of reliable minutiae that can be automatically detected decreases, causing match performance to suffer. This paper presents a novel approach to improving the precision of features that can be extracted from fingerprint images. This is accomplished through improved minutia localization and quality assessment routines that are inspired in part by human visual perception. Initial results have shown an improvement in minutia accuracy for 88.2% of fingerprint minutia sets after applying the proposed localization method. An increase in average quality of true minutiae was found for 98.6% of the fingerprint images when using the proposed quality assessment. The results were obtained using a database of 516 fingerprints with ground truth minutiae.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116532235","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 : 2011-10-11DOI: 10.1109/IJCB.2011.6117495
Haiying Guan, M. Theofanos, Yee-Yin Choong, Brian C. Stanton
Compared with traditional password and other identification methods, biometrics such as face, iris, and fingerprints for automatic personal identification and verification have many advantages, and are increasingly gaining popularity in all kinds of applications. As the technologies mature, the community has begun to realize that usability has great impact on the final accuracy and efficiency of a biometric system. Although research has shown that effective user feedback can improve the quality of the fingerprint images captured and user satisfaction, currently user feedback information of fingerprint devices used in real world applications is very limited. We design a rich, quality-driven interactive real-time user feedback mechanism for unattended fingerprint kiosk. The system aims to improve the quality of biometric samples during the acquisition process by feeding rich information back to the user instantaneously by measuring objective parameters of the image. The paper proposes an innovative, cost-efficient, real-time algorithm for fingertip detection, slap/thumb rotation detection, and finger region intensity estimation. The paper provides detailed information on the technical solution and its implementation. Preliminary results show that the methodology can potentially increase efficiency, effectiveness, and user satisfaction of a fingerprint biometric system.
{"title":"Real-time feedback for usable fingerprint systems","authors":"Haiying Guan, M. Theofanos, Yee-Yin Choong, Brian C. Stanton","doi":"10.1109/IJCB.2011.6117495","DOIUrl":"https://doi.org/10.1109/IJCB.2011.6117495","url":null,"abstract":"Compared with traditional password and other identification methods, biometrics such as face, iris, and fingerprints for automatic personal identification and verification have many advantages, and are increasingly gaining popularity in all kinds of applications. As the technologies mature, the community has begun to realize that usability has great impact on the final accuracy and efficiency of a biometric system. Although research has shown that effective user feedback can improve the quality of the fingerprint images captured and user satisfaction, currently user feedback information of fingerprint devices used in real world applications is very limited. We design a rich, quality-driven interactive real-time user feedback mechanism for unattended fingerprint kiosk. The system aims to improve the quality of biometric samples during the acquisition process by feeding rich information back to the user instantaneously by measuring objective parameters of the image. The paper proposes an innovative, cost-efficient, real-time algorithm for fingertip detection, slap/thumb rotation detection, and finger region intensity estimation. The paper provides detailed information on the technical solution and its implementation. Preliminary results show that the methodology can potentially increase efficiency, effectiveness, and user satisfaction of a fingerprint biometric system.","PeriodicalId":103913,"journal":{"name":"2011 International Joint Conference on Biometrics (IJCB)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121790679","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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