A Novel HMM Decoding Algorithm Permitting Long-Term Dependencies and Its Application to Handwritten Word Recognition

Volkmar Frinken, Ryosuke Kakisako, Seiichi Uchida

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

1 被引用数 (Scopus)

抄録

A new decoding for hidden Markov models is presented. As opposed to the commonly used Viterbi algorithm, it is based on the Min-Cut/Max-Flow algorithm instead of dynamic programming. Therefore non-Markovian long-term dependencies can easily be added to influence the decoding path while still finding the optimal decoding in polynomial time. We demonstrate through an experimental evaluation how these constraints can be used to improve an HMM-based handwritten word recognition system that model words via linear character-HMM by restricting the length of each character.

本文言語英語
ホスト出版物のタイトルProceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014
出版社Institute of Electrical and Electronics Engineers Inc.
ページ128-133
ページ数6
ISBN(電子版)9781479943340
DOI
出版ステータス出版済み - 12月 9 2014
イベント14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014 - Hersonissos, Crete Island, ギリシャ
継続期間: 9月 1 20149月 4 2014

出版物シリーズ

名前Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR
2014-December
ISSN(印刷版)2167-6445
ISSN(電子版)2167-6453

その他

その他14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014
国/地域ギリシャ
CityHersonissos, Crete Island
Period9/1/149/4/14

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンスの応用
  • コンピュータ ビジョンおよびパターン認識

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