Recognition-Based Segmentation of On-Line Cursive Handwriting

NeurIPS 1993 pp. 777-784

/neurips/1993/flann1993neurips-recognitionbased/

Abstract

This paper introduces a new recognition-based segmentation ap(cid:173) proach to recognizing on-line cursive handwriting from a database of 10,000 English words. The original input stream of z, y pen coor(cid:173) dinates is encoded as a sequence of uniform stroke descriptions that are processed by six feed-forward neural-networks, each designed to recognize letters of different sizes. Words are then recognized by performing best-first search over the space of all possible segmen(cid:173) tations. Results demonstrate that the method is effective at both writer dependent recognition (1.7% to 15.5% error rate) and writer independent recognition (5.2% to 31.1% error rate).

PDF NeurIPS Semantic Scholar

Cite

Text

Flann. "Recognition-Based Segmentation of On-Line Cursive Handwriting." Neural Information Processing Systems, 1993.

Markdown

[Flann. "Recognition-Based Segmentation of On-Line Cursive Handwriting." Neural Information Processing Systems, 1993.](https://mlanthology.org/neurips/1993/flann1993neurips-recognitionbased/)

BibTeX

@inproceedings{flann1993neurips-recognitionbased,
  title     = {{Recognition-Based Segmentation of On-Line Cursive Handwriting}},
  author    = {Flann, Nicholas S.},
  booktitle = {Neural Information Processing Systems},
  year      = {1993},
  pages     = {777-784},
  url       = {https://mlanthology.org/neurips/1993/flann1993neurips-recognitionbased/}
}