136 research outputs found

    Robust and applicable handwriting biometrics

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    An examination of quantitative methods for Forensic Signature Analysis and the admissibility of signature verification system as legal evidence.

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    The experiments described in this thesis deal with handwriting characteristics which are involved in the production of forged and genuine signatures and complexity of signatures. The objectives of this study were (1) to provide su?cient details on which of the signature characteristics are easier to forge, (2) to investigate the capabilities of the signature complexity formula given by Found et al. based on a different signature database provided by University of Kent. This database includes the writing movements of 10 writers producing their genuine signature and of 140 writers forging these sample signatures. Using the 150 genuine signatures without constrictions of the Kent’s database an evaluation of the complexity formula suggested in Found et al took place divided the signature in three categories low, medium and high graphical complexity. The results of the formula implementation were compared with the opinions of three leading professional forensic document examiners employed by Key Forensics in the UK. The analysis of data for Study I reveals that there is not ample evidence that high quality forgeries are possible after training. In addition, a closer view of the kinematics of the forging writers is responsible for our main conclusion, that forged signatures are widely different from genuine especially in the kinematic domain. From all the parameters used in this study 11 out of 15 experienced significant changes when the comparison of the two groups (genuine versus forged signature) took place and gave a clear picture of which parameters can assist forensic document examiners and can be used by them to examine the signatures forgeries. The movements of the majority of forgers are signi?cantly slower than those of authentic writers. It is also clearly recognizable that the majority of forgers perform higher levels of pressure when trying to forge the genuine signature. The results of Study II although limited and not entirely consistent with the study of Found that proposed this model, indicate that the model can provide valuable objective evidence (regarding complex signatures) in the forensic environment and justify its further investigation but more work is need to be done in order to use this type of models in the court of law. The model was able to predict correctly only 53% of the FDEs opinion regarding the complexity of the signatures. Apart from the above investigations in this study there will be also a reference at the debate which has started in recent years that is challenging the validity of forensic handwriting experts’ skills and at the effort which has begun by interested parties of this sector to validate and standardise the field of forensic handwriting examination and a discussion started. This effort reveals that forensic document analysis field meets all factors which were set by Daubert ruling in terms of theory proven, education, training, certification, falsifiability, error rate, peer review and publication, general acceptance. However innovative methods are needed for the development of forensic document analysis discipline. Most modern and effective solution in order to prevent observational and emotional bias would be the development of an automated handwriting or signature analysis system. This system will have many advantages in real cases scenario. In addition the significant role of computer-assisted handwriting analysis in the daily work of forensic document examiners (FDE) or the judicial system is in agreement with the assessment of the National Research Council of United States that “the scientific basis for handwriting comparison needs to be strengthened”, however it seems that further research is required in order to be able these systems to reach the accomplishment point of this objective and overcome legal obstacles presented in this study

    My Text in Your Handwriting

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    There are many scenarios where we wish to imitate a specific author’s pen-on-paper handwriting style. Rendering new text in someone’s handwriting is difficult because natural handwriting is highly variable, yet follows both intentional and involuntary structure that makes a person’s style self-consistent. The variability means that naive example-based texture synthesis can be conspicuously repetitive. We propose an algorithm that renders a desired input string in an author’s handwriting. An annotated sample of the author’s handwriting is required; the system is flexible enough that historical documents can usually be used with only a little extra effort. Experiments show that our glyph-centric approach, with learned parameters for spacing, line thickness, and pressure, produces novel images of handwriting that look hand-made to casual observers, even when printed on paper

    Effect of visual feedback on the static and kinetic individual characteristics of handwriting

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    It has been previously established that handwriting is a motor skill defined in a two dimensional spatial domain, consisted of three major levels through which the motor units that contain the letter trajectories are retrieved from their motor memory storage and translated into a process of muscle commands via muscle adjustments. As soon as individuals start learning how to write they are introduced to a writing system common to a group of writers connected by geographic, academic, temporal, national or occupational links. As the writing ability evolves, writers distance themselves from the class system, that they were taught, develop peculiarities in handwriting and acquire personal writing characteristics, the so called individual characteristics of handwriting, which are considered the backbone of forensic handwriting identification. Handwriting is influenced by a number of genetic, physiological and biomechanical factors. Some factors can change the individual's writing so drastically that it may be impossible to make an accurate comparison of the person's normal writing with the person's abnormal writing causing serious problems for forensic document examiners. However the research regarding the visual feedback is partially contradictory regarding the degree of its influence on the individual characteristics. A two-pronged approach was designed in order to investigate the degree of this influence: Samples of signatures, cursive and block handwriting written with and without visual feedback were collected by 40 volunteers and were imported in a PC via an opaque pen tablet using an electronic inking pen. The data was stored and analyzed in a handwriting movement analysis software module specially designed for this research, that was attached in the software MovAlyzeR by Neuroscript LLC. Peer reviewed forensic comparison by a forensic document examined (FDE) between the two groups (that is the group of samples executed with normal visual feedback versus the group of samples executed without visual feedback) shows total lack of significant differences between samples of the two different conditions and the existence of a large corpus of similarities in the design and the pictorial aspect, regardless of the complexity of the samples. Focusing on the cursive and block handwriting, six traits linked to the absence of visual feedback where found: change of overall size, non uniformity of left margins, change of slant, avoidance of pen lifts, inclusion of extra trajectories and decrease of line quality. Furthermore, it was established that the absence of visual feedback by itself cannot lead a trained FDE to an erroneous conclusion. The statistical analysis shows that visual feedback significant influences the duration and average absolute velocity of the signature execution, since the signature is executed more slowly under no visual feedback. Further analysis of the cursive handwriting shows that without visual feedback there is a significant increase in absolute and horizontal size as well as average pen pressure and a decrease in slant and vertical size while in block handwriting there is a significant increase in absolute and horizontal size, average pen pressure as well as duration and a decrease in slant, average absolute velocity and vertical size. The comparative analysis suggests that the factors of gender, educational level and handedness creates an insignificant influence during the comparison of the two conditions of the researched individual characteristics, with the only notable exception of the relationship between signature duration and educational level due to automation and its results in the memory retrieval program of the allographs. The combination of the above findings suggests that all types of writing (signature, cursive and block handwriting) are governed by a single major open loop motor program, which is not significantly influenced by visual feedback -no evidence was found that visual feedback intervenes significantly in the procedure of allograph execution, but is mainly linked with the auxiliary order of macro-managing, inspection and possibly correction of the overall outcome of the combination of the above allographs

    Writer Identification of Arabic Handwritten Documents

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    Writer Identification of Arabic Handwritten Documents

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    Advances in Character Recognition

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    This book presents advances in character recognition, and it consists of 12 chapters that cover wide range of topics on different aspects of character recognition. Hopefully, this book will serve as a reference source for academic research, for professionals working in the character recognition field and for all interested in the subject

    Searching for Dead Sea Scribes:a study on using Artificial Intelligence and palaeography for writer identification in correlation with spelling and scribal practices, codicology, handwriting quality, and literary classification systems for Dead Sea Scrolls

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    My study explores the Dead Sea Scrolls through the lens of individual scribes. Specifically, the practices of individual scribes responsible for penningtwo or more of the Oumran manuscripts. It utilises innovative digital palaeographic methods alongside traditional palaeographic approaches for scribalidentification. It gathers previously un-gathered data on the handwriting, spelling practices, codicological features and literary content of individual scribes. The study explores how this data on scribes both supports and challenges various aspects of theories in the field of Dead Sea Scroll studies, which accept a a sectarian origin for the Qumran manuscripts
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