293 research outputs found

    Information Preserving Processing of Noisy Handwritten Document Images

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    Many pre-processing techniques that normalize artifacts and clean noise induce anomalies due to discretization of the document image. Important information that could be used at later stages may be lost. A proposed composite-model framework takes into account pre-printed information, user-added data, and digitization characteristics. Its benefits are demonstrated by experiments with statistically significant results. Separating pre-printed ruling lines from user-added handwriting shows how ruling lines impact people\u27s handwriting and how they can be exploited for identifying writers. Ruling line detection based on multi-line linear regression reduces the mean error of counting them from 0.10 to 0.03, 6.70 to 0.06, and 0.13 to 0.02, com- pared to an HMM-based approach on three standard test datasets, thereby reducing human correction time by 50%, 83%, and 72% on average. On 61 page images from 16 rule-form templates, the precision and recall of form cell recognition are increased by 2.7% and 3.7%, compared to a cross-matrix approach. Compensating for and exploiting ruling lines during feature extraction rather than pre-processing raises the writer identification accuracy from 61.2% to 67.7% on a 61-writer noisy Arabic dataset. Similarly, counteracting page-wise skew by subtracting it or transforming contours in a continuous coordinate system during feature extraction improves the writer identification accuracy. An implementation study of contour-hinge features reveals that utilizing the full probabilistic probability distribution function matrix improves the writer identification accuracy from 74.9% to 79.5%

    INJURY-INDUCED HAND DOMINANCE TRANSFER

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    Hand dominance is the preferential use of one hand over the other for motor tasks. 90% of people are right-hand dominant, and the majority of injuries (acute and cumulative trauma) occur to the dominant limb, creating a double-impact injury whereby a person is left in a functional state of single-handedness and must rely on the less-dexterous, non-dominant hand. When loss of dominant hand function is permanent, a forced shift of dominance is termed injury-induced hand dominance transfer (I-IHDT). Military service members injured in combat operation may face I-IHDT following mutilating injuries (crush, avulsion, burn and blast wounds) that result in dominant limb amputation or limb salvage. Military occupational therapy practitioners utilize an intervention called Handwriting For Heroes to facilitate hand dominance transfer. This intervention trains the injured military member how to write again using the previously non-dominant hand. Efficacy and clinical effectiveness studies were needed to validate the use of this intervention. This dissertation contains three studies related to I-IHDT. One study measured handwriting performance in adults who previously (greater than 2 years ago) lost function of their dominant hands. Results verified that handwriting performance, when measured on two separate occasions (six-weeks apart) was similar (stable). A second study examined the efficacy of Handwriting For Heroes in non-impaired participants. Results demonstrated a positive effect on the variables that measured the written product: legibility, writing speed (letters-per-minute); as well as a positive effect on the variables that measured the writing process: kinematic and kinetic parameters. The final study examined the clinical effectiveness of Handwriting For Heroes in an injured military population. Results did not show as positive results as the efficacy study, despite similar compliance with the intervention. Specifically, non-impaired participants started with faster writing speeds in their non-dominant hands (higher letters-per-minute) and made more gains (wider ranges). The non-impaired participants also started with faster dexterity (betters scores on the Grooved Pegboard) but they made fewer gains than the injured service members (smaller ranges). Nevertheless, injured participants clearly made gains in all dependent variables thereby demonstrating clinical effectiveness of the interventio

    Approaching real time dynamic signature verification from a systems and control perspective.

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    Student Number : 9901877H MSc Dissertation School of Electrical and Information Engineering Faculty of Engineering and the Built Environmentalgorithm. The origins of handwriting idiosyncrasies and habituation are explained using systems theory, and it is shown that the 2/3 power law governing biomechanics motion also applies to handwriting. This leads to the conclusion that it is possible to derive handwriting velocity profiles from a static image, and that a successful forgery of a signature is only possible in the event of the forger being able to generate a signature using natural ballistic motion. It is also shown that significant portion of the underlying dynamic system governing the generation of handwritten signatures can be inferred by deriving time segmented transfer function models of the x and y co-ordinate velocity profiles of a signature. The prototype algorithm consequently developed uses x and y components of pen-tip velocity profiles (vx[n] and vy[n]) to create signature representations based on autoregression-with-exogenous-input (ARX) models. Verification is accomplished using a similarity measure based on the results of a k-step ahead predictor and 5 complementary metrics. Using 350 signatures collected from 21 signers, the system’s false acceptance (FAR) and false rejection (FRR) rates were 2.19% and 27.05% respectively. This high FRR is a result of measurement inadequacies, and it is believed that the algorithm’s FRR is approximately 18%

    Naval Reserve support to information Operations Warfighting

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    Since the mid-1990s, the Fleet Information Warfare Center (FIWC) has led the Navy's Information Operations (IO) support to the Fleet. Within the FIWC manning structure, there are in total 36 officer and 84 enlisted Naval Reserve billets that are manned to approximately 75 percent and located in Norfolk and San Diego Naval Reserve Centers. These Naval Reserve Force personnel could provide support to FIWC far and above what they are now contributing specifically in the areas of Computer Network Operations, Psychological Operations, Military Deception and Civil Affairs. Historically personnel conducting IO were primarily reservists and civilians in uniform with regular military officers being by far the minority. The Naval Reserve Force has the personnel to provide skilled IO operators but the lack of an effective manning document and training plans is hindering their opportunity to enhance FIWC's capabilities in lull spectrum IO. This research investigates the skill requirements of personnel in IO to verify that the Naval Reserve Force has the talent base for IO support and the feasibility of their expanded use in IO.http://archive.org/details/navalreservesupp109451098

    Efficient Learning Machines

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    Computer scienc

    Kodikologie und Paläographie im digitalen Zeitalter 2 - Codicology and Palaeography in the Digital Age 2

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    Der Einsatz digitaler Technik verändert den wissenschaftlichen Umgang mit der handgeschriebenen Überlieferung. Dieser Band vertieft Fragen zu Digitalisierung und Katalogisierung, zu automatischer Schrifterkennung und Schriftanalyse, und er erweitert eine Diskussion, die mit dem im letzten Jahr erschienenen ersten Band zur digitalen Handschriftenforschung angestossen worden ist: Welche Erkenntnisse können etwa naturwissenschaftliche Methoden liefern? Welche musik- und kunsthistorischen Fragestellungen lassen sich mit Hilfe moderner Informationstechnologien beantworten? Wie lassen sich Methoden einer digitalen Auswertung lateinischer Handschriften auf griechische, glagolithische oder ägyptische Texte anwenden? Der raum-zeitliche Rahmen der hier von einer internationalen Autorenschaft zusammengetragenen 22 wissenschaftlichen Beiträge reicht vom alten Ägypten bis ins Paris der Postmoderne. Mit Beiträgen von: Pádraig Ó Macháin; Armand Tif; Alison Stones, Ken Sochats; Melissa Terras; Silke Schöttle, Ulrike Mehringer; Marilena Maniaci, Paolo Eleuteri; Ezio Ornato; Toby Burrows; Robert Kummer; Lior Wolf, Nachum Dershowitz, Liza Potikha, Tanya German, Roni Shweka, Yacov Choueka; Daniel Deckers, Leif Glaser; Timothy Stinson; Peter Meinlschmidt, Carmen Kämmerer, Volker Märgner; Peter Stokes—Dominique Stutzmann; Stephen Quirke; Markus Diem, Robert Sablatnig, Melanie Gau, Heinz Miklas; Julia Craig-McFeely; Isabelle Schürch, Martin Rüesch; Carole Dornier, Pierre-Yves Buard; Samantha Saidi, Jean-François Bert, Philippe Artières; Elena Pierazzo, Peter Stokes. Einleitung von: Franz Fischer, Patrick Sahle. Unter Mitarbeit von: Bernhard Assmann, Malte Rehbein, Patrick Sahle
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