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Edson J R Justino - One of the best experts on this subject based on the ideXlab platform.

  • off line signature verification based on forensic questioned Document Examination approach
    ACM Symposium on Applied Computing, 2007
    Co-Authors: Cesar R Santos, Flavio Bortolozzi, Luiz S Oliveira, Edson J R Justino
    Abstract:

    There are different methods for signature verification proposed in the literature. Most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. This is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. In this paper we propose an off-line signature verification method based on Forensic Questioned Document Examination approach. This kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. Comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.

  • SAC - Off-line signature verification based on forensic questioned Document Examination approach
    Proceedings of the 2007 ACM symposium on Applied computing - SAC '07, 2007
    Co-Authors: Cesar R Santos, Flavio Bortolozzi, Luiz S Oliveira, Edson J R Justino
    Abstract:

    There are different methods for signature verification proposed in the literature. Most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. This is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. In this paper we propose an off-line signature verification method based on Forensic Questioned Document Examination approach. This kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. Comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.

Cesar R Santos - One of the best experts on this subject based on the ideXlab platform.

  • off line signature verification based on forensic questioned Document Examination approach
    ACM Symposium on Applied Computing, 2007
    Co-Authors: Cesar R Santos, Flavio Bortolozzi, Luiz S Oliveira, Edson J R Justino
    Abstract:

    There are different methods for signature verification proposed in the literature. Most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. This is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. In this paper we propose an off-line signature verification method based on Forensic Questioned Document Examination approach. This kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. Comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.

  • SAC - Off-line signature verification based on forensic questioned Document Examination approach
    Proceedings of the 2007 ACM symposium on Applied computing - SAC '07, 2007
    Co-Authors: Cesar R Santos, Flavio Bortolozzi, Luiz S Oliveira, Edson J R Justino
    Abstract:

    There are different methods for signature verification proposed in the literature. Most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. This is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. In this paper we propose an off-line signature verification method based on Forensic Questioned Document Examination approach. This kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. Comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.

Flavio Bortolozzi - One of the best experts on this subject based on the ideXlab platform.

  • CIARP - Forensic Document Examination: Who Is the Writer?
    Progress in Pattern Recognition Image Analysis Computer Vision and Applications, 2018
    Co-Authors: Aline Maria Malachini Miotto Amaral, Flavio Bortolozzi, Cinthia Obladen De Almendra Freitas, Yandre M G Costa
    Abstract:

    This work presents a baseline system to automatic handwriting identification based only on graphometric features. Initially a set composed of 12 features was presented and its extraction process demonstrated. In order to evaluate the efficiency of these features, a selection process was applied, and a smaller group composed only of 4 features (GS = Goodness Subset) present the best writer identification rates. Experiments were conducted in order to evaluate the performance, individually and in group, of the graphometric features; and to identify the number of writers that significantly affect the accuracy of the system. The accuracy of the system applied to 100 different writers taking account the GS features set were 84% (TOP1), 96% (TOP5) and 98% (TOP10). These results are comparable to others in the literature on graphometric features. It can be observed that gradually the relation between the number of writers and accuracy is stabilized, and with 200 writers the results are maintained.

  • forensic Document Examination who is the writer
    Iberoamerican Congress on Pattern Recognition, 2017
    Co-Authors: Aline Maria Malachini Miotto Amaral, Flavio Bortolozzi, Cinthia Obladen De Almendra Freitas, Yandre M G Costa
    Abstract:

    This work presents a baseline system to automatic handwriting identification based only on graphometric features. Initially a set composed of 12 features was presented and its extraction process demonstrated. In order to evaluate the efficiency of these features, a selection process was applied, and a smaller group composed only of 4 features (GS = Goodness Subset) present the best writer identification rates. Experiments were conducted in order to evaluate the performance, individually and in group, of the graphometric features; and to identify the number of writers that significantly affect the accuracy of the system. The accuracy of the system applied to 100 different writers taking account the GS features set were 84% (TOP1), 96% (TOP5) and 98% (TOP10). These results are comparable to others in the literature on graphometric features. It can be observed that gradually the relation between the number of writers and accuracy is stabilized, and with 200 writers the results are maintained.

  • off line signature verification based on forensic questioned Document Examination approach
    ACM Symposium on Applied Computing, 2007
    Co-Authors: Cesar R Santos, Flavio Bortolozzi, Luiz S Oliveira, Edson J R Justino
    Abstract:

    There are different methods for signature verification proposed in the literature. Most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. This is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. In this paper we propose an off-line signature verification method based on Forensic Questioned Document Examination approach. This kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. Comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.

  • SAC - Off-line signature verification based on forensic questioned Document Examination approach
    Proceedings of the 2007 ACM symposium on Applied computing - SAC '07, 2007
    Co-Authors: Cesar R Santos, Flavio Bortolozzi, Luiz S Oliveira, Edson J R Justino
    Abstract:

    There are different methods for signature verification proposed in the literature. Most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. This is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. In this paper we propose an off-line signature verification method based on Forensic Questioned Document Examination approach. This kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. Comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.

Luiz S Oliveira - One of the best experts on this subject based on the ideXlab platform.

  • off line signature verification based on forensic questioned Document Examination approach
    ACM Symposium on Applied Computing, 2007
    Co-Authors: Cesar R Santos, Flavio Bortolozzi, Luiz S Oliveira, Edson J R Justino
    Abstract:

    There are different methods for signature verification proposed in the literature. Most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. This is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. In this paper we propose an off-line signature verification method based on Forensic Questioned Document Examination approach. This kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. Comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.

  • SAC - Off-line signature verification based on forensic questioned Document Examination approach
    Proceedings of the 2007 ACM symposium on Applied computing - SAC '07, 2007
    Co-Authors: Cesar R Santos, Flavio Bortolozzi, Luiz S Oliveira, Edson J R Justino
    Abstract:

    There are different methods for signature verification proposed in the literature. Most of them, take into account a personal model, i.e., they need a considerable number of genuine signatures of the same writer to correctly train the model. This is the main drawback of this kind of approach, since in real applications we have small number of samples available for training. In this paper we propose an off-line signature verification method based on Forensic Questioned Document Examination approach. This kind of strategy reduces any classification problem to a 2-class problem, hence, makes it possible to build robust signature verification systems even when few signatures per writer are available. Comprehensive results on a database composed of 240 writers (40 samples per writer) demonstrate the efficiency of the proposed method.

Adel M. Alimi - One of the best experts on this subject based on the ideXlab platform.

  • Towards a novel biometric system for forensic Document Examination
    Computers & Security, 2020
    Co-Authors: Thameur Dhieb, Sourour Njah, Houcine Boubaker, Wael Ouarda, Mounir Ben Ayed, Adel M. Alimi
    Abstract:

    Abstract Biometric systems have demonstrated an important enhancement in writer identification from online handwriting. Indeed, writer identification is still a challenging task in the definition of a set of features able to characterize the different samples of handwriting Documents. These samples are not usually stable and show a vast variability from the same writer over time, or from different writers. The ability to identify the Documents’ authors provides more chances for using these Documents for various purposes and especially in forensic analysis. In this paper, we present a biometric based recognition system for forensic Document Examination capable of identifying a Document's author. This system consists of the preprocessing and the segmentation of online handwriting into a sequence of strokes in a first step. Then, from each stroke, we extract a set of static and dynamic features. Next, all the segments which are composed of two consecutive strokes are categorized into groups and subgroups according to their position and their geometric characteristics. Finally, Deep Neural Network is used as a classifier. Experiments which are conducted on IBM_UB_1, IAM OnDB, NLPR Handwriting and ADAB databases, demonstrate that the proposed system outperforms the existing writer identification systems on Latin and Arabic scripts. This justifies its usefulness in forensic Examination of handwriting.