Handwriting is a complex human activity that engages a blend of cognitive and visual motor skills. Current understanding of the neural correlates of handwriting has largely come from lesion studies of patients with impaired handwriting. Task-based fMRI studies would be useful to supplement this work. To address concerns over ecological validity, previously we developed a fMRI-compatible, comput...

Human movement modeling can be of great interest for the design of pattern recognition systems relying on the understanding of the fine motor control (such as on-line handwriting recognition or signature verification) as well as for the development of intelligent systems involving in a way or another the processing of human movements. In this paper, we briefly list the different models that hav...

This paper reviews the current state of the art in handwriting recognition research. The paper deals with issues such as hand-printed character and cursive handwritten word recognition. It describes recent achievements, difficulties, successes and challenges in all aspects of handwriting recognition. It also presents a new approach which dramatically improves current handwriting recognition sys...

This paper describes the design, acquisition process and baseline evaluation of the new e-BioSign database, which includes dynamic signature and handwriting information. Data is acquired from 5 different COTS devices: three Wacom devices (STU-500, STU-530 and DTU-1031) specifically designed to capture dynamic signatures and handwriting, and two general purpose tablets (Samsung Galaxy Note 10.1 ...

Failure to attain handwriting competency during the school-age years often has far-reaching negative effects on both academic success and self-esteem. This complex occupational task has many underlying component skills that may interfere with handwriting performance. Fine motor control, bilateral and visual-motor integration, motor planning, in-hand manipulation, proprioception, visual percepti...

We present an approach of the problem of handwriting recognition using hidden Markov random fields and based on a trully bidimensional analysis of the handwriting. The main innovative aspect of this approah is the combination of a windowed analysis of the image, a Markovian modelisation and an implementation of the 2D dynamic programming algorithm that achieves a fast and optimal decoding of Ma...

A public domain optical character recognition (OCR) system has been developed by the National Institute of Standards and Technology (NIST) to provide a baseline of performance on off-line handwriting recognition from forms. The system’s source code, training data, and performance assessment tools are all publicly available. The system recognizes the handprint written on Handwriting Sample Forms...

Aims: The present study was designed to provide a basis for teachers and therapists to better understand primary school children’s handwriting problems in the face of the complex relationships that exist between literacy skills with the goal to contribute to treatment choices. Original Research Article Bosga-Stork et al.; BJESBS, 12(1): 1-13, 2016; Article no.BJESBS.20703 2 Study Design: A long...

The study of the link between handwriting and personality is known as analysis. It a specific manner using to convey one’s cognitive process. That’s why it’s also “brain writing”. Handwriting, like person’s fingerprint, unique trait that cannot be duplicated by two distinct people. aids us in determining emotional state. Handwriting recognition usually done traditional manner, which professiona...

If the influence of visual-motor integration (copying forms) on the quality of handwriting has been widely investigated, the influence of eye-hand coordination (tracing item) has been less well analyzed. The Concise Assessment Scale for Children’s Handwriting (BHK), the Developmental Test of Visual Perception (DTVP-2), and the section “Manual Dexterity” of the Movement Assessment Battery for Ch...