Recovery of writing sequence of static images of handwriting using UWM

K. K. Lau, Pong Chi YUEN, Yuan Y. Tang

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

It is generally agreed that an on-line recognition system is always reliable than an off-line one. It is due to the availability of the dynamic information, especially the writing sequence of the strokes. This paper presents a new statistical method to reconstruct the writing order of a handwritten script from a two-dimensional static image. The reconstruction process consists of two phases, named the training phase and the testing phase. In the training phase, the writing order with other attributes, such as length and direction, are extracted from a set of training on-line handwritten scripts statistically to form a universal writing model (UWM). In the testing phase, UWM is applied to reconstruct the drawing order of offline handwritten scripts by finding the highest total probability. 300 off-line signatures with ground truth are used for evaluation. Experimental results show that the reconstructed writing sequence using UWM is close to the actual writing sequence.

Original languageEnglish
Title of host publicationProceedings - 7th International Conference on Document Analysis and Recognition, ICDAR 2003
PublisherIEEE Computer Society
Pages1123-1128
Number of pages6
ISBN (Electronic)0769519601
DOIs
Publication statusPublished - 2003
Event7th International Conference on Document Analysis and Recognition, ICDAR 2003 - Edinburgh, United Kingdom
Duration: 3 Aug 20036 Aug 2003

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2003-January
ISSN (Print)1520-5363

Conference

Conference7th International Conference on Document Analysis and Recognition, ICDAR 2003
Country/TerritoryUnited Kingdom
CityEdinburgh
Period3/08/036/08/03

Scopus Subject Areas

  • Computer Vision and Pattern Recognition

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