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

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

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

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

Research output: Contribution to conference › Paper › peer-review

Abstract

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.

Original language	English
Pages	39-44
Number of pages	6
Publication status	Published - 2005
Externally published	Yes
Event	1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005 - Seoul, Korea, Republic of Duration: 2005 Aug 29 → 2005 Aug 29

Conference

Conference	1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005
Country/Territory	Korea, Republic of
City	Seoul
Period	05/8/29 → 05/8/29

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Software

Cite this

Grayscale feature combination in recognition based segmentation for degraded text string recognition. / Sun, Jun; Hotta, Yoshinobu; Fujimoto, Katsuhito et al.
2005. 39-44 Paper presented at 1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005, Seoul, Korea, Republic of.

Research output: Contribution to conference › Paper › peer-review

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author = "Jun Sun and Yoshinobu Hotta and Katsuhito Fujimoto and Katsuyama Yutaka and Satoshi Naoi",

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language = "English",

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note = "1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005 ; Conference date: 29-08-2005 Through 29-08-2005",

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AU - Hotta, Yoshinobu

AU - Fujimoto, Katsuhito

AU - Yutaka, Katsuyama

AU - Naoi, Satoshi

PY - 2005

Y1 - 2005

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AB - 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.

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T2 - 1st International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2005

Y2 - 29 August 2005 through 29 August 2005

ER -

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

Abstract

Conference

ASJC Scopus subject areas

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