ML Anthology

Recognition of Handwritten Word: First and Second Order Hidden Markov Model Based Approach

Amlan Kundu, Yang He, Paramvir Bahl
CVPR 1988 pp. 457-462
doi:10.1109/CVPR.1988.196275 /cvpr/1988/kundu1988cvpr-recognition/

Abstract

The handwritten word recognition problem is modeled in the framework of the hidden Markov model (HMM). The states of HMM are identified with the letters of the alphabet. The optimum symbols are then generated experimentally using 15 different features. Both the first- and second-order HMMs are proposed for the recognition tasks. Using the existing statistical knowledge of English, the calculation scheme of the model parameters are immensely simplified. Once the model is established, the Viterbi algorithm is used to recognize the sequence of letters consisting the word. Some experimental results are also provided indicating the success of the scheme.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Kundu et al. "Recognition of Handwritten Word: First and Second Order Hidden Markov Model Based Approach." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1988. doi:10.1109/CVPR.1988.196275

Markdown

[Kundu et al. "Recognition of Handwritten Word: First and Second Order Hidden Markov Model Based Approach." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1988.](https://mlanthology.org/cvpr/1988/kundu1988cvpr-recognition/) doi:10.1109/CVPR.1988.196275

BibTeX

@inproceedings{kundu1988cvpr-recognition,
  title     = {{Recognition of Handwritten Word: First and Second Order Hidden Markov Model Based Approach}},
  author    = {Kundu, Amlan and He, Yang and Bahl, Paramvir},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1988},
  pages     = {457-462},
  doi       = {10.1109/CVPR.1988.196275},
  url       = {https://mlanthology.org/cvpr/1988/kundu1988cvpr-recognition/}
}