Grayscale feature combination in recognition based segmentation for degraded text string recognition

Jun Sun, Yoshinobu Hotta, Katsuhito Fujimoto, Katsuyama Yutaka, Satoshi Naoi

研究成果: Paper

3 被引用数 (Scopus)

抄録

Grayscale feature is very effective for degraded character recognition. While many papers focus on different feature extraction algorithms on single character recognition, few deals with the impact of the selected feature on segmentation. For recognition-based segmentation, a good recognition performance on single character may not always have good performance on segmentation. In this paper, two types of grayscale feature, the R-Feature and the S-Feature, are proposed based on dual-eigenspace decomposition. The RFeature is suitable for single character recognition. The SFeature is suitable for text string segmentation. These two feature are combined to further improve the performance for degraded Japanese text string recognition.

本文言語English
ページ39-44
ページ数6
出版ステータスPublished - 2005
イベント1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005 - Seoul, Korea, Republic of
継続期間: 2005 8 292005 8 29

Conference

Conference1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005
CountryKorea, Republic of
CitySeoul
Period05/8/2905/8/29

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Software

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