Binary tree-based precision-keeping clustering for very fast Japanese character recognition

Yohei Sobu, Hideaki Goto, Hirotomo Aso

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

Real-time character recognition in video frames has been attracting great attention from developers since scene text recognition was recognized as a new field of Optical Character Recognition (OCR) applications. Some oriental languages such as Japanese and Chinese have thousands of characters, and the character recognition takes much longer time in general compared with European languages. Speed-up of character recognition is crucial to develop software for mobile devices such as Smart Phones. This paper proposes a binary tree-based clustering technique that can keep the precision as quite high as possible. The experimental results show that the character recognition using the proposed clustering technique is 8.3 times faster than the full linear matching at mere 0.22% precision drop. When the proposed method is combined with the Sequential Similarity Detection Algorithm (SSDA) and a PCA-based dimensionality reduction, we can achieve 36.2 times faster character matching at 0.29% precision drop.

本文言語English
ホスト出版物のタイトルIVCNZ 2010 - 25th International Conference of Image and Vision Computing New Zealand
DOI
出版ステータスPublished - 2010 12 1
イベント25th International Conference of Image and Vision Computing New Zealand, IVCNZ 2010 - Queenstown, New Zealand
継続期間: 2010 11 82010 11 9

出版物シリーズ

名前International Conference Image and Vision Computing New Zealand
ISSN(印刷版)2151-2191
ISSN(電子版)2151-2205

Other

Other25th International Conference of Image and Vision Computing New Zealand, IVCNZ 2010
CountryNew Zealand
CityQueenstown
Period10/11/810/11/9

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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