Earticle

초록

영어

An approach to online handwriting word recognition using segmentation-based techniques is presented in this paper. This approach is referred to as lexicon-driven approach because an optimal segmentation is generated for each string in the lexicon. Word recognition problem is transformed into matching optimization problems between the dictionary entry and the handwritten word image. The segmentation processes use these steps such as removing delayed strokes, shape analysis of the stroke trajectory, reconstructing delayed strokes and combining adjacent fragments. Dynamic matching is used to ranking the lexicon entries in order to get best match. A match score is assigned to a segmentation and string by matching each segment to the corresponding character in the string with a character recognition algorithm that returns confidence value for each character class. As a result the performance for lexicons of size 10, 100, 500 and 1000are 93.17%, 70.33%, 59.79%，51.20% and 94.85%, 79.75%, 74.42%, 62.19% for adding distance and normalizing distance respectively.

목차

Abstract
 1. Introduction
 2. Word Recognition System Overview
 3. Segmentation
  3.1. Over Segmentation
  3.2. Construct Segmentation Network
 4. Character Confidence Assignment
 5. Recognition
  5.1. Problem Formulation
  5.2. Dynamic Programming Matching
 6. Experimental Result
  6.1. Acquisition of Online Word Image Data
  6.2. Experimental Result
  6.3. Error Analysis
 7. Conclusion
 Acknowledgements
 References

키워드

저자

• Mayire Ibrayim [ Postdoctoral Research Station of Computer Science and Technology, Xinjiang University, Urumqi, China 830046, ]
• Askar Hamdulla [ School of Software, Xinjiang University, Urumqi, China 830046 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605