{"title":"Hierarchically linked extended features in fingerprints","authors":"K. Mieloch, A. Munk, P. Mihăilescu","doi":"10.1109/BSYM.2008.4655522","DOIUrl":"https://doi.org/10.1109/BSYM.2008.4655522","url":null,"abstract":"Requirements for identifying and defining additional fingerprint features beyond minutiae, even not limited to level 3 details, has already been addressed by the community . However, new feature proposals are based on refinements of existing features (e.g. a finer level of classification), or on the introduction of new single features (e.g. 3-D level features such as the ridge height) . The new set of features proposed in this work does not only include additional fingerprint features individually but it also contains the information about their relationships such as line adjacency information at minutiae points or links between neighboring fingerprint lines. The dual information, that is the interference between ridges and valleys, is included as well. For the first confirmation of the quality of extracted features in application for the matching, the goodness of the extracted minutiae has been tested. The experiments have shown a decreased error rate when applying the minutiae to a standard minutiae-based matcher.","PeriodicalId":389538,"journal":{"name":"2008 Biometrics Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129260025","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}
{"title":"A client-entropy measure for On-line Signatures","authors":"S.G. Salicetti, N. Houmani, B. Dorizzi","doi":"10.1109/BSYM.2008.4655527","DOIUrl":"https://doi.org/10.1109/BSYM.2008.4655527","url":null,"abstract":"In this article, we propose an original way to characterize information content in online signatures through a client-entropy measure based on local density estimation by a hidden Markov model. We show that this measure can be used to categorize signatures in visually coherent classes that can be related to complexity and variability criteria. Besides, the generated categories are coherent across four different databases: BIOMET, MCYT-100, BioSecure data subsets DS2 and DS3. This measure allows a comparison of databases in terms of clientspsila signatures according to their information content.","PeriodicalId":389538,"journal":{"name":"2008 Biometrics Symposium","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133921455","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}
{"title":"Scars, marks and tattoos (SMT): Soft biometric for suspect and victim identification","authors":"Jung-Eun Lee, A.K. Jain, Rong Jin","doi":"10.1109/BSYM.2008.4655515","DOIUrl":"https://doi.org/10.1109/BSYM.2008.4655515","url":null,"abstract":"Scars, marks and tattoos (SMT) are being increasingly used for suspect and victim identification in forensics and law enforcement agencies. Tattoos, in particular, are getting serious attention because of their visual and demographic characteristics as well as their increasing prevalence. However, current tattoo matching procedure requires human-assigned class labels in the ANSI/NIST ITL 1-2000 standard which makes it time consuming and subjective with limited retrieval performance. Further, tattoo images are complex and often contain multiple objects with large intra-class variability, making it very difficult to assign a single category in the ANSI/NIST standard. We describe a content-based image retrieval (CBIR) system for matching and retrieving tattoo images. Based on scale invariant feature transform (SIFT) features extracted from tattoo images and optional accompanying demographical information, our system computes feature-based similarity between the query tattoo image and tattoos in the criminal database. Experimental results on two different tattoo databases show encouraging results.","PeriodicalId":389538,"journal":{"name":"2008 Biometrics Symposium","volume":"26 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131239968","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}
S. Kanade, D. Camara, E. Krichen, D. Petrovska-Delacrétaz, B. Dorizzi
{"title":"Three factor scheme for biometric-based cryptographic key regeneration using iris","authors":"S. Kanade, D. Camara, E. Krichen, D. Petrovska-Delacrétaz, B. Dorizzi","doi":"10.1109/BSYM.2008.4655523","DOIUrl":"https://doi.org/10.1109/BSYM.2008.4655523","url":null,"abstract":"In this paper we propose a three factor (smart card, iris code and password) scheme for cryptographic key regeneration based on fuzzy sketches idea which handles biometric variability with error correcting codes. Because errors in iris codes have mixed nature (random and burst errors), concatenated Hadamard and Reed-Solomon codes are used in this work. Hadamard codes can correct up to 25% errors but experiments showed that it is necessary to increase this capacity. In order to correct this higher amount of errors, a zero padding scheme is introduced. In addition, a user specific iris code shuffling key is used which increases the separation between genuine and impostor Hamming distance distributions, providing better separability between genuine users and impostors. We succeeded in regenerating a 198-bit key with estimated entropy of 83 bits on the NIST-ICE database at 0.055% False Acceptance Rate (FAR) and 1.04% False Rejection Rate (FRR).","PeriodicalId":389538,"journal":{"name":"2008 Biometrics Symposium","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114459040","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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