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Proceedings ArticleDOI

Temporal clues in handwriting

TLDR
This paper presents work on the extraction of temporal information from static images of handwriting and its implications for character recognition.
Abstract
Handwritten character recognition is typically classified as online or offline depending on the nature of the input data. Online data consists of a temporal sequence of instrument positions while offline data is in the form of a 2D image of the writing sample. Online recognition techniques have been relatively successful but have the disadvantage of requiring the data to be gathered during the writing process. This paper presents work on the extraction of temporal information from static images of handwriting and its implications for character recognition. >

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Citations
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Journal ArticleDOI

Recovery of drawing order from single-stroke handwriting images

TL;DR: By recovering a drawing order of a handwritten script, the temporal information can be recovered from a static 2D image and this method will be used as a bridge from the offline handwriting character recognition problem to the online one.
Book ChapterDOI

Cursive Word Recognition: Methods and Strategies

TL;DR: This paper aims to present the basic principles of the techniques used so far and to classify them according to the type of strategy they are based on, mainly on off-line recognition although most of the strategies presented here are also valid for on- line recognition.
Proceedings ArticleDOI

Techniques for static handwriting trajectory recovery: a survey

TL;DR: An overview and discussion of pen trajectory recovery methods developed to date is presented and the temporal order of the strokes or the pen trajectory is shown to be more promising for recovery.
Proceedings ArticleDOI

Recovery of drawing order from scanned images of multi-stroke handwriting

TL;DR: By recovering the drawing order of a handwritten script, the temporal information can be recovered from a scanned image and this method can be used as a bridge from the offline handwriting character recognition problem to the online one.
Journal ArticleDOI

Comparative Study of Habitual with Left and Right Handwritings of The Same Person

TL;DR: This study collected accustomed and unaccustomed handwritings from the elementary school teachers in Bangkok and showed that 75% of the subjects have similarity in narrow-size letter.
References
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Proceedings ArticleDOI

Offline tracing and representation of signatures

TL;DR: An approach for representing signatures in an offline environment using a multiresolution critical-point segmentation method to extract local feature points, at varying degrees of scale and coarseness, for subsequent representation of the signature.