Hierarchical decomposition of handwriting deformation vector field using 2D warping and global/local affine transformation

Toru Wakahara, Seiichi Uchida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper addresses the basic problem of how to extract, describe, and evaluate handwriting deformation from not the statistical but the deterministic viewpoint. The key ideas are threefold. The first idea is to apply 2D warping to extraction of handwriting deformation vector field (DVF) between a pair of input and target images. The second idea is to hierarchically decompose the DVF by a parametric deformation model of global/local affine transformation. As a result, the DVF is expressed by a series of deformation components each of which is characterized by a window size of local affine transformation. The third idea is interrupting of the series of deformation components to obtain natural, reasonable handwriting deformation. Experiments using the handwritten numeral database IPTP CDROM1B show that 31.1% of the handwriting DVF is expressed by global affine transformation, and the subsequent few local affine transformations successfully discriminate natural handwriting deformation from unnatural one.

Original languageEnglish
Title of host publicationICDAR2009 - 10th International Conference on Document Analysis and Recognition
Pages1141-1145
Number of pages5
DOIs
Publication statusPublished - Dec 10 2009
EventICDAR2009 - 10th International Conference on Document Analysis and Recognition - Barcelona, Spain
Duration: Jul 26 2009Jul 29 2009

Publication series

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

Other

OtherICDAR2009 - 10th International Conference on Document Analysis and Recognition
CountrySpain
CityBarcelona
Period7/26/097/29/09

Fingerprint

Decomposition
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Cite this

Wakahara, T., & Uchida, S. (2009). Hierarchical decomposition of handwriting deformation vector field using 2D warping and global/local affine transformation. In ICDAR2009 - 10th International Conference on Document Analysis and Recognition (pp. 1141-1145). [5277583] (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR). https://doi.org/10.1109/ICDAR.2009.33

Hierarchical decomposition of handwriting deformation vector field using 2D warping and global/local affine transformation. / Wakahara, Toru; Uchida, Seiichi.

ICDAR2009 - 10th International Conference on Document Analysis and Recognition. 2009. p. 1141-1145 5277583 (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wakahara, T & Uchida, S 2009, Hierarchical decomposition of handwriting deformation vector field using 2D warping and global/local affine transformation. in ICDAR2009 - 10th International Conference on Document Analysis and Recognition., 5277583, Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, pp. 1141-1145, ICDAR2009 - 10th International Conference on Document Analysis and Recognition, Barcelona, Spain, 7/26/09. https://doi.org/10.1109/ICDAR.2009.33
Wakahara T, Uchida S. Hierarchical decomposition of handwriting deformation vector field using 2D warping and global/local affine transformation. In ICDAR2009 - 10th International Conference on Document Analysis and Recognition. 2009. p. 1141-1145. 5277583. (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR). https://doi.org/10.1109/ICDAR.2009.33
Wakahara, Toru ; Uchida, Seiichi. / Hierarchical decomposition of handwriting deformation vector field using 2D warping and global/local affine transformation. ICDAR2009 - 10th International Conference on Document Analysis and Recognition. 2009. pp. 1141-1145 (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR).
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