Pub Date : 2014-12-01DOI: 10.1109/CIBIM.2014.7015453
Mohammad Haghighat, M. Abdel-Mottaleb, W. Alhalabi
In this paper, we present a computationally efficient statistical face modeling approach. The efficiency of our proposed approach is the result of mathematical simplifications in the core formula of a previous face modeling method and the use of the singular value decomposition. In order to reduce the errors in our resulting models, we preprocess the facial images to normalize for pose and illumination and remove little occlusions. Then, the statistical face models for the enrolled subjects are obtained from the normalized face images. The effects of the variations in pose, facial expression, and illumination on the accuracy of the system are studied. Experimental results demonstrate the reduction in the computational complexity of the new approach and its efficacy in modeling the face images.
{"title":"Computationally efficient statistical face model in the feature space","authors":"Mohammad Haghighat, M. Abdel-Mottaleb, W. Alhalabi","doi":"10.1109/CIBIM.2014.7015453","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015453","url":null,"abstract":"In this paper, we present a computationally efficient statistical face modeling approach. The efficiency of our proposed approach is the result of mathematical simplifications in the core formula of a previous face modeling method and the use of the singular value decomposition. In order to reduce the errors in our resulting models, we preprocess the facial images to normalize for pose and illumination and remove little occlusions. Then, the statistical face models for the enrolled subjects are obtained from the normalized face images. The effects of the variations in pose, facial expression, and illumination on the accuracy of the system are studied. Experimental results demonstrate the reduction in the computational complexity of the new approach and its efficacy in modeling the face images.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121215726","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015449
M. Sultana, M. Gavrilova, R. Alhajj, S. Yanushkevich
Quality variations of samples significantly affect the performance of biometric recognition systems. In case of face recognition systems, illumination degradation is the most common contributor of enormous intra-class variation. Wavelet transforms are very popular techniques for face or object recognition from images due to their illumination insensitiveness. However, low and high frequency subbands of wavelet transforms do not possess equal insensitiveness to different degree of illumination change. In this paper, we investigated the illumination insensitiveness of the subbands of Dual-Tree Complex Wavelet Transform (DTCWT) at different scales. Based on the investigations, a novel face recognition system has been proposed using weighted fusion of low and high frequency subbands that can adapt extensive illumination variations and produces high recognition rate even with a single sample. A novel fuzzy weighting scheme has been proposed to determine the adaptive weights during uncertain illuminations conditions. In addition, an adaptive normalization approach has been applied for illumination quality enhancement of the poor lit samples while retaining the quality of good samples. The performance of the proposed adaptive method has been evaluated on Extended Yale B and AR face databases. Experimental results exhibit significant performance improvement of the proposed adaptive face recognition approach over benchmark methods under extensive illumination change.
{"title":"Adaptive multi-stream score fusion for illumination invariant face recognition","authors":"M. Sultana, M. Gavrilova, R. Alhajj, S. Yanushkevich","doi":"10.1109/CIBIM.2014.7015449","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015449","url":null,"abstract":"Quality variations of samples significantly affect the performance of biometric recognition systems. In case of face recognition systems, illumination degradation is the most common contributor of enormous intra-class variation. Wavelet transforms are very popular techniques for face or object recognition from images due to their illumination insensitiveness. However, low and high frequency subbands of wavelet transforms do not possess equal insensitiveness to different degree of illumination change. In this paper, we investigated the illumination insensitiveness of the subbands of Dual-Tree Complex Wavelet Transform (DTCWT) at different scales. Based on the investigations, a novel face recognition system has been proposed using weighted fusion of low and high frequency subbands that can adapt extensive illumination variations and produces high recognition rate even with a single sample. A novel fuzzy weighting scheme has been proposed to determine the adaptive weights during uncertain illuminations conditions. In addition, an adaptive normalization approach has been applied for illumination quality enhancement of the poor lit samples while retaining the quality of good samples. The performance of the proposed adaptive method has been evaluated on Extended Yale B and AR face databases. Experimental results exhibit significant performance improvement of the proposed adaptive face recognition approach over benchmark methods under extensive illumination change.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116619763","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015455
Tao Yang, J. Stahl, S. Schuckers, Fang Hua
Image mosaicking technology, as an image processing technology that can aggregate the information from a sequence of images, has been used to process large size images. In this paper, we are trying to apply the mosaicking technology to nonideal iris recognition study. The proposed algorithm composes the information from a collection of iris images, and generates a “composite” image. The experiment includes the partial blinking iris and subregion of off-angle iris images. The contribution of this paper is to show the image mosaicking is an effective technology for nonideal iris recognition at the condition of limited pattern information.
{"title":"Subregion mosaicking applied to nonideal iris recognition","authors":"Tao Yang, J. Stahl, S. Schuckers, Fang Hua","doi":"10.1109/CIBIM.2014.7015455","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015455","url":null,"abstract":"Image mosaicking technology, as an image processing technology that can aggregate the information from a sequence of images, has been used to process large size images. In this paper, we are trying to apply the mosaicking technology to nonideal iris recognition study. The proposed algorithm composes the information from a collection of iris images, and generates a “composite” image. The experiment includes the partial blinking iris and subregion of off-angle iris images. The contribution of this paper is to show the image mosaicking is an effective technology for nonideal iris recognition at the condition of limited pattern information.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"239-240 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116847381","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015457
Hengyi Zhang, Chaoying Tang, X. Li, A. Kong
Vein patterns have been used in commercial biometric systems for many years and are recently considered for criminal authentication. Understanding the similarity between genetically identical vein patterns is important, especially when using them in legal cases involving identical twins. Vein patterns sharing the same Deoxyribonucleic acid (DNA) sequence are generally regarded as vein patterns with maximum similarity. If they are completely distinguishable, it implies that the uniqueness of vein patterns is high. Though the genetic dependence of other biometric traits, including fingerprints, faces, palmprints, and irises, have been studied, genetically identical vein patterns have not been studied systematically. With the help of an automatic vein pattern matching algorithm, this paper analyzes and measures the similarity between genetically identical vein patterns. 234 genetically identical forearm pairs and 204 genetically identical thigh pairs were collected for this study. Experimental results indicate that genetically identical vein patterns have extra similarity, but they are distinguishable.
{"title":"A study of similarity between genetically identical body vein patterns","authors":"Hengyi Zhang, Chaoying Tang, X. Li, A. Kong","doi":"10.1109/CIBIM.2014.7015457","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015457","url":null,"abstract":"Vein patterns have been used in commercial biometric systems for many years and are recently considered for criminal authentication. Understanding the similarity between genetically identical vein patterns is important, especially when using them in legal cases involving identical twins. Vein patterns sharing the same Deoxyribonucleic acid (DNA) sequence are generally regarded as vein patterns with maximum similarity. If they are completely distinguishable, it implies that the uniqueness of vein patterns is high. Though the genetic dependence of other biometric traits, including fingerprints, faces, palmprints, and irises, have been studied, genetically identical vein patterns have not been studied systematically. With the help of an automatic vein pattern matching algorithm, this paper analyzes and measures the similarity between genetically identical vein patterns. 234 genetically identical forearm pairs and 204 genetically identical thigh pairs were collected for this study. Experimental results indicate that genetically identical vein patterns have extra similarity, but they are distinguishable.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127299617","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015445
Abhijit Das, U. Pal, M. A. Ferrer-Ballester, M. Blumenstein
In this piece of work a wrist vein pattern recognition and verification system is proposed. Here the wrist vein images from the PUT database were used, which were acquired in visible spectrum. The vein image only highlights the vein pattern area so, segmentation was not required. Since the wrist's veins are not prominent, image enhancement was performed. An Adaptive Histogram Equalization and Discrete Meyer Wavelet were used to enhance the vessel patterns. For feature extraction, the vein pattern is characterized with Dense Local Binary Pattern (D-LBP). D-LBP patch descriptors of each training image are used to form a bag of features, which was used to produce the training model. Support Vector Machines (SVMs) were used for classification. An encouraging Equal Error Rate (EER) of 0.79% was achieved in our experiments.
本文提出了一种腕部静脉模式识别与验证系统。本文使用PUT数据库中的腕静脉图像，这些图像是在可见光谱中获得的。静脉图像只突出静脉图案区域，因此不需要分割。由于腕部静脉不明显，因此进行了图像增强。采用自适应直方图均衡化和离散Meyer小波增强血管模式。在特征提取方面，采用密集局部二值模式(Dense Local Binary pattern, D-LBP)进行特征提取。每个训练图像的D-LBP补丁描述符被用来形成一个特征包，用来生成训练模型。支持向量机(svm)用于分类。在我们的实验中获得了令人鼓舞的0.79%的等错误率(EER)。
{"title":"A new wrist vein biometric system","authors":"Abhijit Das, U. Pal, M. A. Ferrer-Ballester, M. Blumenstein","doi":"10.1109/CIBIM.2014.7015445","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015445","url":null,"abstract":"In this piece of work a wrist vein pattern recognition and verification system is proposed. Here the wrist vein images from the PUT database were used, which were acquired in visible spectrum. The vein image only highlights the vein pattern area so, segmentation was not required. Since the wrist's veins are not prominent, image enhancement was performed. An Adaptive Histogram Equalization and Discrete Meyer Wavelet were used to enhance the vessel patterns. For feature extraction, the vein pattern is characterized with Dense Local Binary Pattern (D-LBP). D-LBP patch descriptors of each training image are used to form a bag of features, which was used to produce the training model. Support Vector Machines (SVMs) were used for classification. An encouraging Equal Error Rate (EER) of 0.79% was achieved in our experiments.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123228564","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015442
George S. Eskander, R. Sabourin, Eric Granger
An offline signature-based fuzzy vault (OSFV) is a bio-cryptographic implementation that uses handwritten signature images as biometrics instead of traditional passwords to secure private cryptographic keys. Having a reliable OSFV implementation is the first step towards automating financial and legal authentication processes, as it provides greater security of sensitive documents by means of the embedded handwritten signatures. The authors have recently proposed the first OSFV implementation, where a machine learning approach based on the dissimilarity representation concept is employed to select a reliable feature representation adapted for the fuzzy vault scheme. In this paper, some variants of this system are proposed for enhanced accuracy and security. In particular, a new method that adapts user key size is presented. Performance of proposed methods are compared using the Brazilian PUCPR and GPDS signature databases and results indicate that the key-size adaptation method achieves a good compromise between security and accuracy. As the average system entropy is increased from 45-bits to about 51-bits, the AER (average error rate) is decreased by about 21%.
{"title":"Offline signature-based fuzzy vault: A review and new results","authors":"George S. Eskander, R. Sabourin, Eric Granger","doi":"10.1109/CIBIM.2014.7015442","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015442","url":null,"abstract":"An offline signature-based fuzzy vault (OSFV) is a bio-cryptographic implementation that uses handwritten signature images as biometrics instead of traditional passwords to secure private cryptographic keys. Having a reliable OSFV implementation is the first step towards automating financial and legal authentication processes, as it provides greater security of sensitive documents by means of the embedded handwritten signatures. The authors have recently proposed the first OSFV implementation, where a machine learning approach based on the dissimilarity representation concept is employed to select a reliable feature representation adapted for the fuzzy vault scheme. In this paper, some variants of this system are proposed for enhanced accuracy and security. In particular, a new method that adapts user key size is presented. Performance of proposed methods are compared using the Brazilian PUCPR and GPDS signature databases and results indicate that the key-size adaptation method achieves a good compromise between security and accuracy. As the average system entropy is increased from 45-bits to about 51-bits, the AER (average error rate) is decreased by about 21%.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134202101","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015452
D. Gorodnichy, S. Yanushkevich, V. Shmerko
This paper introduces a formalization of the Automated Border Control (ABC) machines deployed worldwide as part of the eBorder infrastructure for automated traveller clearance. Proposed formalization includes classification of the eBorder technologies, definition of the basic components of the ABC machines, identification of their key properties, establishment of metrics for their evaluation and comparison, as well as development of a dedicated architecture based on the assistant-based concept. Specifically, three generations of the ABC machines are identified: Gen-1 ABC machines which are biometric enabled kiosks, such as Canada's NEXUS or UK IRIS, to process low-risk pre-enrolled travellers; Gen-2 ABC machines which are eGate systems to serve travellers with biometric eID / ePassports; and Gen-3 ABC machines that will be working to support the eBorder process of the future. These ABC machines are compared in this paper based on certain criteria, such as availability of the dedicated architectural components, and in terms of the life-cycle performance metrics. This paper addresses the related problems of deployment and evaluation of the ABC technologies and machines, including the vulnerability analysis and strategic planning of the eBorder infrastructure.
{"title":"Automated border control: Problem formalization","authors":"D. Gorodnichy, S. Yanushkevich, V. Shmerko","doi":"10.1109/CIBIM.2014.7015452","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015452","url":null,"abstract":"This paper introduces a formalization of the Automated Border Control (ABC) machines deployed worldwide as part of the eBorder infrastructure for automated traveller clearance. Proposed formalization includes classification of the eBorder technologies, definition of the basic components of the ABC machines, identification of their key properties, establishment of metrics for their evaluation and comparison, as well as development of a dedicated architecture based on the assistant-based concept. Specifically, three generations of the ABC machines are identified: Gen-1 ABC machines which are biometric enabled kiosks, such as Canada's NEXUS or UK IRIS, to process low-risk pre-enrolled travellers; Gen-2 ABC machines which are eGate systems to serve travellers with biometric eID / ePassports; and Gen-3 ABC machines that will be working to support the eBorder process of the future. These ABC machines are compared in this paper based on certain criteria, such as availability of the dedicated architectural components, and in terms of the life-cycle performance metrics. This paper addresses the related problems of deployment and evaluation of the ABC technologies and machines, including the vulnerability analysis and strategic planning of the eBorder infrastructure.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130359012","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015461
Diego D. Alves, G. Cruz, C. Vinhal
This work presents a user's authentication system for computational environments based on keystroke dynamics. The methodology proposed is low-cost, non-intrusive and can be applied in areas of monitored access software to increase the level of data security. The algorithm works by monitoring the typing of the user in real time, capturing split times in which the key was pressed and released. Five characteristics are captured in this entry: The ASCII code (American Standard Code for Information Interchange), three splits associated and a duration associated with the key, which would be the time that it remained pressed. From this data it was possible to trace metrics that were able to identify the user in question. Results obtained show a high level of accuracy.
{"title":"Authentication system using behavioral biometrics through keystroke dynamics","authors":"Diego D. Alves, G. Cruz, C. Vinhal","doi":"10.1109/CIBIM.2014.7015461","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015461","url":null,"abstract":"This work presents a user's authentication system for computational environments based on keystroke dynamics. The methodology proposed is low-cost, non-intrusive and can be applied in areas of monitored access software to increase the level of data security. The algorithm works by monitoring the typing of the user in real time, capturing split times in which the key was pressed and released. Five characteristics are captured in this entry: The ASCII code (American Standard Code for Information Interchange), three splits associated and a duration associated with the key, which would be the time that it remained pressed. From this data it was possible to trace metrics that were able to identify the user in question. Results obtained show a high level of accuracy.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129921310","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015443
Kamlesh Tiwari, A. Nigam, Phalguni Gupta
This paper proposes a score level fusion scheme for a multimodal biometric system. Accuracy and reliability of a system are improved by utilizing more than one samples. Every matching of a biometric sample with its corresponding biometric sample in the database produces a matching score. There multiple scores from different biometric samples are fused for further utilization. It proposes an efficient threshold alignment and range compression scheme for score normalization. It uses statistical properties of biometric score distribution. The proposed scheme has been tested over a multimodal database which is constructed by using three publicly available database viz. FVC2006-DB2-A of fingerprint, CASIA-V4-Lamp of iris and PolyU of palmprint. Experimental results have shown the significant performance boost.
{"title":"TARC: A novel score fusion scheme for multimodal biometric systems","authors":"Kamlesh Tiwari, A. Nigam, Phalguni Gupta","doi":"10.1109/CIBIM.2014.7015443","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015443","url":null,"abstract":"This paper proposes a score level fusion scheme for a multimodal biometric system. Accuracy and reliability of a system are improved by utilizing more than one samples. Every matching of a biometric sample with its corresponding biometric sample in the database produces a matching score. There multiple scores from different biometric samples are fused for further utilization. It proposes an efficient threshold alignment and range compression scheme for score normalization. It uses statistical properties of biometric score distribution. The proposed scheme has been tested over a multimodal database which is constructed by using three publicly available database viz. FVC2006-DB2-A of fingerprint, CASIA-V4-Lamp of iris and PolyU of palmprint. Experimental results have shown the significant performance boost.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130881583","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 : 2014-12-01DOI: 10.1109/CIBIM.2014.7015459
Nhat Quang Huynh, Xingpeng Xu, A. Kong, S. Subbiah
Because of recent advances in imaging technology, the use of image-based evidences, such as faces and tattoos, is increasing dramatically. Face and tattoo images of prisoners are collected regularly for suspect image database establishment. New biometric traits such as skin marks, androgenic hairs, and blood vessels hidden in color images are getting more attention because they are shown to be useful for criminal and victim identification, especially when their faces and tattoos are neither observable nor available. The current manual approach of collecting images of prisoners is extremely time consuming and does not record these new biometric traits. To address this problem, an unprecedented full-body imaging system is developed. Furthermore, an automatic and systematic routine based on the system for effectively collecting prisoners' images is proposed. This paper concentrates on the system hardware design as well as its image collecting and processing capability. The system has been used to collect and process more than 30,000 infrared and color images from 188 subjects. Its performance is very encouraging.
{"title":"A preliminary report on a full-body imaging system for effectively collecting and processing biometric traits of prisoners","authors":"Nhat Quang Huynh, Xingpeng Xu, A. Kong, S. Subbiah","doi":"10.1109/CIBIM.2014.7015459","DOIUrl":"https://doi.org/10.1109/CIBIM.2014.7015459","url":null,"abstract":"Because of recent advances in imaging technology, the use of image-based evidences, such as faces and tattoos, is increasing dramatically. Face and tattoo images of prisoners are collected regularly for suspect image database establishment. New biometric traits such as skin marks, androgenic hairs, and blood vessels hidden in color images are getting more attention because they are shown to be useful for criminal and victim identification, especially when their faces and tattoos are neither observable nor available. The current manual approach of collecting images of prisoners is extremely time consuming and does not record these new biometric traits. To address this problem, an unprecedented full-body imaging system is developed. Furthermore, an automatic and systematic routine based on the system for effectively collecting prisoners' images is proposed. This paper concentrates on the system hardware design as well as its image collecting and processing capability. The system has been used to collect and process more than 30,000 infrared and color images from 188 subjects. Its performance is very encouraging.","PeriodicalId":432938,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127087741","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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