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 |
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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 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 05/8/29 → 05/8/29 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Software