Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449689
P. Staroniewicz
The paper presents speaker verification results for six basic emotional states. The database of emotional speech (six acted states: anger, sadness, happiness, fear, disgust, surprise) plus the neutral state were examined with a typical speaker verification system based on MFCC features and GMM classifiers. The obtained results were confronted with the subjective and objective emotion recognition scores. The significant influence of emotion on speaker recognition scores is substantially bigger for emotions with a strong activation factor.
{"title":"Considering basic emotional state information in speaker verification","authors":"P. Staroniewicz","doi":"10.1109/IWBF.2016.7449689","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449689","url":null,"abstract":"The paper presents speaker verification results for six basic emotional states. The database of emotional speech (six acted states: anger, sadness, happiness, fear, disgust, surprise) plus the neutral state were examined with a typical speaker verification system based on MFCC features and GMM classifiers. The obtained results were confronted with the subjective and objective emotion recognition scores. The significant influence of emotion on speaker recognition scores is substantially bigger for emotions with a strong activation factor.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129553466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449693
M. Almeida, P. Correia, P. Larsen
Forensic experts, police officers and others working with forensic video analysis can benefit from more "intelligent" video handling tools, such as automatic event/face detection, for instance to help search the relevant video footage prior to the actual case work. The ideal would be to have access to tailor-made software, based on state of art knowledge in fields such as soft biometrics, gait recognition, photogrammetry, etc. This paper proposes an open and extensible platform, BioFoV (Biometric Forensic Video tool), for forensic video analysis and biometric data extraction, aiming to host some of the developments that researchers come up with for solving specific problems, but that are often not shared with the community. BioFoV includes a simple to use Graphical User Interface (GUI), is implemented with open software that can run in multiple software platforms, and its implementation is publicly available.
{"title":"BioFoV – an open platform for forensic video analysis and biometric data extraction","authors":"M. Almeida, P. Correia, P. Larsen","doi":"10.1109/IWBF.2016.7449693","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449693","url":null,"abstract":"Forensic experts, police officers and others working with forensic video analysis can benefit from more \"intelligent\" video handling tools, such as automatic event/face detection, for instance to help search the relevant video footage prior to the actual case work. The ideal would be to have access to tailor-made software, based on state of art knowledge in fields such as soft biometrics, gait recognition, photogrammetry, etc. This paper proposes an open and extensible platform, BioFoV (Biometric Forensic Video tool), for forensic video analysis and biometric data extraction, aiming to host some of the developments that researchers come up with for solving specific problems, but that are often not shared with the community. BioFoV includes a simple to use Graphical User Interface (GUI), is implemented with open software that can run in multiple software platforms, and its implementation is publicly available.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128733151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449694
Evangelia Pantraki, Constantine Kotropoulos, A. Lanitis
Important problems in speech soft biometrics include the prediction of speaker's age or gender. Here, the aforementioned problems are addressed in the context of utterances collected during a long time period. A unified framework for age and gender prediction is proposed based on Parallel Factor Analysis 2 (PARAFAC2). PARAFAC2 is applied to a collection of three matrices, namely the speech utterance-feature matrix whose columns are the auditory cortical representations, the speaker age matrix whose columns are indicator vectors of suitable dimension, and the speaker gender matrix whose columns are proper indicator vectors associated to speaker's gender. PARAFAC2 is able to reduce the dimensionality of the auditory cortical representations by projecting these representations onto a semantic space dominated by the age and the gender concepts, yielding a sketch (i.e., a feature vector of reduced dimensions). To predict speaker's age interval associated to a test utterance, the speech utterance sketch is pre-multiplied by the left singular vectors of the speaker age matrix. To predict the gender of the speaker who uttered any test utterance, the speech utterance sketch is pre-multiplied by the left singular vectors of the speaker gender matrix. In both cases, a ranking vector is obtained that is exploited for decision making. Promising results are demonstrated, when the aforementioned framework is applied to the Trinity College Dublin Speaker Ageing Database.
{"title":"Age interval and gender prediction using PARAFAC2 applied to speech utterances","authors":"Evangelia Pantraki, Constantine Kotropoulos, A. Lanitis","doi":"10.1109/IWBF.2016.7449694","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449694","url":null,"abstract":"Important problems in speech soft biometrics include the prediction of speaker's age or gender. Here, the aforementioned problems are addressed in the context of utterances collected during a long time period. A unified framework for age and gender prediction is proposed based on Parallel Factor Analysis 2 (PARAFAC2). PARAFAC2 is applied to a collection of three matrices, namely the speech utterance-feature matrix whose columns are the auditory cortical representations, the speaker age matrix whose columns are indicator vectors of suitable dimension, and the speaker gender matrix whose columns are proper indicator vectors associated to speaker's gender. PARAFAC2 is able to reduce the dimensionality of the auditory cortical representations by projecting these representations onto a semantic space dominated by the age and the gender concepts, yielding a sketch (i.e., a feature vector of reduced dimensions). To predict speaker's age interval associated to a test utterance, the speech utterance sketch is pre-multiplied by the left singular vectors of the speaker age matrix. To predict the gender of the speaker who uttered any test utterance, the speech utterance sketch is pre-multiplied by the left singular vectors of the speaker gender matrix. In both cases, a ranking vector is obtained that is exploited for decision making. Promising results are demonstrated, when the aforementioned framework is applied to the Trinity College Dublin Speaker Ageing Database.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133047096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449682
Guney Kayim, Ekberjan Derman, A. A. Salah
This paper describes a novel biometric scenario, where a person is authenticated at an ATM, and has to be re-identified from a camera within a very short time period, under very challenging illumination and pose conditions, and using data from a single session. The application scenario is the automatic retraction of forgotten card or cash at an ATM, which happens frequently, and causes inconvenience to users and loss of profits for the banks. We propose a multimodal authentication system that operates under the constraints imposed by this applications scenario, and implement face recognition and color based body appearance recognition to create a system that improves ATM behavior in case of forgotten card or cash by re-identifying the user from an embedded ATM camera. We focus on the scenario and the platform, and report tests with the proposed system under challenging conditions, obtained from ATMs placed in the field.
{"title":"Short term re-identification of Automatic Teller Machine (ATM) users via face and body appearance features","authors":"Guney Kayim, Ekberjan Derman, A. A. Salah","doi":"10.1109/IWBF.2016.7449682","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449682","url":null,"abstract":"This paper describes a novel biometric scenario, where a person is authenticated at an ATM, and has to be re-identified from a camera within a very short time period, under very challenging illumination and pose conditions, and using data from a single session. The application scenario is the automatic retraction of forgotten card or cash at an ATM, which happens frequently, and causes inconvenience to users and loss of profits for the banks. We propose a multimodal authentication system that operates under the constraints imposed by this applications scenario, and implement face recognition and color based body appearance recognition to create a system that improves ATM behavior in case of forgotten card or cash by re-identifying the user from an embedded ATM camera. We focus on the scenario and the platform, and report tests with the proposed system under challenging conditions, obtained from ATMs placed in the field.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123438833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449692
Michael Kalbitz, T. Scheidat, C. Vielhauer
Both in biometric and forensic sciences, handwriting modality plays an important role. While in biometrics, the sub-discipline of online analysis utilises recordings of the actual writing process, offline analysis has a close link to handwriting forensics. In the later domain, goals comprise for example writer identification or uncover indented writing of found writing traces on documents. In this paper we study the general feasibility of a new approach to handwriting forensics by means of three contact-less non-destructive 2D/3D optical sensors providing high resolution images in the nanometer range which have already shown great potential for the digitised crime scene forensics e.g for fingerprints or gun cartridges. We perform a three-step concept: First, in a general sensor review we identify one sensor which appears most appropriate for our initial use cases, along with appropriate parametrization. Secondly, we propose a first test setup for the acquisition of handwriting traces on paper. The corresponding data is captured from the first and second layer of a five sheets paper stack. Thirdly, we present and discuss our first results of digital image pre-processing based on topographic information representing the pen pressure during the writing process. Our pre-processing approach is focused on segmenting the writing trace in topographical data. For segmentation of the trace we apply different linear filter like mean or binomial as well as non-linear filter like median.
{"title":"First investigation of feasibility of contact-less non-destructive optical sensors to detect, acquire and digitally process forensic handwriting based on pressure information","authors":"Michael Kalbitz, T. Scheidat, C. Vielhauer","doi":"10.1109/IWBF.2016.7449692","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449692","url":null,"abstract":"Both in biometric and forensic sciences, handwriting modality plays an important role. While in biometrics, the sub-discipline of online analysis utilises recordings of the actual writing process, offline analysis has a close link to handwriting forensics. In the later domain, goals comprise for example writer identification or uncover indented writing of found writing traces on documents. In this paper we study the general feasibility of a new approach to handwriting forensics by means of three contact-less non-destructive 2D/3D optical sensors providing high resolution images in the nanometer range which have already shown great potential for the digitised crime scene forensics e.g for fingerprints or gun cartridges. We perform a three-step concept: First, in a general sensor review we identify one sensor which appears most appropriate for our initial use cases, along with appropriate parametrization. Secondly, we propose a first test setup for the acquisition of handwriting traces on paper. The corresponding data is captured from the first and second layer of a five sheets paper stack. Thirdly, we present and discuss our first results of digital image pre-processing based on topographic information representing the pen pressure during the writing process. Our pre-processing approach is focused on segmenting the writing trace in topographical data. For segmentation of the trace we apply different linear filter like mean or binomial as well as non-linear filter like median.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123461456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449674
L. Debiasi, A. Uhl
Identifying the source camera which acquired a given image using the cameras PRNU is a well established task in image forensics, known as camera or device identification. Since digital image sensors are widely used to acquire biometric data, it is eligible that this task can also be performed with biometric sensors and the respective data. This has already been studied in literature. In this paper we focus on a slightly different task, which consists in clustering images acquired with the same sensor in a data set possibly containing images from an unknown number of biometric sensors. Previous work showed unclear results that have been difficult to interpret because of the low quality of the extracted PRNU. In this paper we compare the use of a PRNU enhancement technique to the use of special uncorrelated images acquired with known biometric sensors in this clustering context. We additionally propose extensions of existing source sensor attribution techniques using data from known sensors. Finally, the results of the enhancement approaches and the results using the uncorrelated data acquired with the known sensors are compared and an assessment on whether multiple sensor instances have been used in the different investigated data sets is given.
{"title":"Comparison of PRNU enhancement techniques to generate PRNU fingerprints for biometric source sensor attribution","authors":"L. Debiasi, A. Uhl","doi":"10.1109/IWBF.2016.7449674","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449674","url":null,"abstract":"Identifying the source camera which acquired a given image using the cameras PRNU is a well established task in image forensics, known as camera or device identification. Since digital image sensors are widely used to acquire biometric data, it is eligible that this task can also be performed with biometric sensors and the respective data. This has already been studied in literature. In this paper we focus on a slightly different task, which consists in clustering images acquired with the same sensor in a data set possibly containing images from an unknown number of biometric sensors. Previous work showed unclear results that have been difficult to interpret because of the low quality of the extracted PRNU. In this paper we compare the use of a PRNU enhancement technique to the use of special uncorrelated images acquired with known biometric sensors in this clustering context. We additionally propose extensions of existing source sensor attribution techniques using data from known sensors. Finally, the results of the enhancement approaches and the results using the uncorrelated data acquired with the known sensors are compared and an assessment on whether multiple sensor instances have been used in the different investigated data sets is given.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123122860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449681
R. Kuzu, Koray Balci, A. A. Salah
Users of online social networks often use multiple identities. This paper investigates the possibility of identifying a user from his or her chat behavior in such a setting. We have collected a large corpus of multiparty chat records in Turkish, obtained from a multiplayer game database. The most active 978 users are selected according to their participation in game chat sessions. This corpus is used in a biometric identification experiment where we seek each user among a gallery of users. Character matrices for each player are used as features, and re-centered local profiles and cosine similarity measure are preferred as identification methods. We systematically assess the effect of text normalization on identification. We report comparative results, the best of which reach around 75% rank-1 accuracy for a gallery size of 978.
{"title":"Authorship recognition in a multiparty chat scenario","authors":"R. Kuzu, Koray Balci, A. A. Salah","doi":"10.1109/IWBF.2016.7449681","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449681","url":null,"abstract":"Users of online social networks often use multiple identities. This paper investigates the possibility of identifying a user from his or her chat behavior in such a setting. We have collected a large corpus of multiparty chat records in Turkish, obtained from a multiplayer game database. The most active 978 users are selected according to their participation in game chat sessions. This corpus is used in a biometric identification experiment where we seek each user among a gallery of users. Character matrices for each player are used as features, and re-centered local profiles and cosine similarity measure are preferred as identification methods. We systematically assess the effect of text normalization on identification. We report comparative results, the best of which reach around 75% rank-1 accuracy for a gallery size of 978.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124899480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449678
Filipe Guapo, P. Correia, D. Meuwly, D. V. D. Vloed
In recent years there has been an increase in the offer of commercial software tools for forensic evaluation of biometric evidence. The important role these tools are meant to play requires that these are subject to a rigorous and careful validation process. This has spurred guidelines and procedures through which the validation should be processed. In this work we describe the validation procedure of a commercial Likelihood Ratio computation tool while proposing a new approach to performance evaluation. This is done by testing not only the tool alongside a single baseline method but several baseline methods which have previously been validated by the community. The tool is tested with over 90000 speaker recognition scores and its performance is analyzed and compared to well-known methods, it is shown that the use of multiple baseline methods increases the amount of information and context. This improves decision making in the validation process and helps safeguarding against outliers.
{"title":"Empirical validation of likelihood ratio methods – A case study in forensic speaker recognition","authors":"Filipe Guapo, P. Correia, D. Meuwly, D. V. D. Vloed","doi":"10.1109/IWBF.2016.7449678","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449678","url":null,"abstract":"In recent years there has been an increase in the offer of commercial software tools for forensic evaluation of biometric evidence. The important role these tools are meant to play requires that these are subject to a rigorous and careful validation process. This has spurred guidelines and procedures through which the validation should be processed. In this work we describe the validation procedure of a commercial Likelihood Ratio computation tool while proposing a new approach to performance evaluation. This is done by testing not only the tool alongside a single baseline method but several baseline methods which have previously been validated by the community. The tool is tested with over 90000 speaker recognition scores and its performance is analyzed and compared to well-known methods, it is shown that the use of multiple baseline methods increases the amount of information and context. This improves decision making in the validation process and helps safeguarding against outliers.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114752416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449684
N. Yadav, Solange Rossato, Juliette Kahn, J. Bonastre
Speaker voice characteristics are an important aspect of forensic phonetics. Previous studies have suggested that all the features present in the speech signals are not equally important for speaker discrimination, and it is well-known that subsets of phonemes are more informative than others. However, most of theses studies have concerned a whole group of speakers, without taking into account the speaker specificities. This paper presents a framework for the selection of a subset of phonemes from the speech signal at the speaker level in order to capture the speaker variability in this selection process. We present the approach for the selection of the most discriminatory phonemes and a preliminary study have been performed on French reading speech database. At the global level, the most discriminatory phonemes are compared to previous studies. At the speaker level, we have examined the inter-speaker variability according to their most discriminatory phonemes. The experimental results verified the effectiveness of the proposed framework.
{"title":"Speaker specific features and phonemes in speech: a proposal for evaluating a possible interaction","authors":"N. Yadav, Solange Rossato, Juliette Kahn, J. Bonastre","doi":"10.1109/IWBF.2016.7449684","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449684","url":null,"abstract":"Speaker voice characteristics are an important aspect of forensic phonetics. Previous studies have suggested that all the features present in the speech signals are not equally important for speaker discrimination, and it is well-known that subsets of phonemes are more informative than others. However, most of theses studies have concerned a whole group of speakers, without taking into account the speaker specificities. This paper presents a framework for the selection of a subset of phonemes from the speech signal at the speaker level in order to capture the speaker variability in this selection process. We present the approach for the selection of the most discriminatory phonemes and a preliminary study have been performed on French reading speech database. At the global level, the most discriminatory phonemes are compared to previous studies. At the speaker level, we have examined the inter-speaker variability according to their most discriminatory phonemes. The experimental results verified the effectiveness of the proposed framework.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127446381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-03DOI: 10.1109/IWBF.2016.7449686
Tasmina Islam, M. Fairhurst
The analysis of handwritten signatures is an area of ongoing and increasing interest for both biometrics and forensics researchers. Hesitation in writing execution, estimated (to a large degree) through human inspection, has been commonly used by Forensic Document Examiners (FDE) or Forensic Handwriting Experts (FHE) as one of the important features which may be used to distinguish between genuine signatures and imitations or forgeries. This paper introduces some simple objective measures of hesitation and investigates their reliability and efficacy in automating the analysis of handwritten signatures for forensic or biometric applications.
{"title":"Investigating an objective measure of writer hesitation for forensic analysis of the handwritten signature","authors":"Tasmina Islam, M. Fairhurst","doi":"10.1109/IWBF.2016.7449686","DOIUrl":"https://doi.org/10.1109/IWBF.2016.7449686","url":null,"abstract":"The analysis of handwritten signatures is an area of ongoing and increasing interest for both biometrics and forensics researchers. Hesitation in writing execution, estimated (to a large degree) through human inspection, has been commonly used by Forensic Document Examiners (FDE) or Forensic Handwriting Experts (FHE) as one of the important features which may be used to distinguish between genuine signatures and imitations or forgeries. This paper introduces some simple objective measures of hesitation and investigates their reliability and efficacy in automating the analysis of handwritten signatures for forensic or biometric applications.","PeriodicalId":282164,"journal":{"name":"2016 4th International Conference on Biometrics and Forensics (IWBF)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132043914","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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