Abstract
Text extraction and recognition from still and moving images have many important applications. But, when a source image is an ordinary natural scene, text extraction becomes very complicated and difficult. In this paper, we suggest text extraction methods based on color and gray information. The method using the color image is processed by color reduction, color clustering, and text region extraction and verifications. The method using the gray-level image is processed by edge detection, long line removal, repetitive run-length smearing (RLS), and text region extraction and verifications. Combining two approaches improves the extraction accuracies both in simple and in complex images. Also, estimating skew and perspective of the extracted text regions are considered.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Publisher | Springer Verlag |
| Pages | 329-340 |
| Number of pages | 12 |
| Volume | 2423 |
| ISBN (Print) | 3540440682, 9783540440680 |
| Publication status | Published - 2002 |
| Event | 5th International Workshop on Document Analysis Systems, DAS 2002 - Princeton, United States Duration: 2002 Aug 19 → 2002 Aug 21 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 2423 |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 5th International Workshop on Document Analysis Systems, DAS 2002 |
|---|---|
| Country | United States |
| City | Princeton |
| Period | 02/8/19 → 02/8/21 |
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ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
Scene text extraction in complex images. / Byun, Hye Ran; Roh, Myung Cheol; Kim, Kil Cheon; Choi, Yeong Woo; Lee, Seong Whan.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2423 Springer Verlag, 2002. p. 329-340 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2423).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Scene text extraction in complex images
AU - Byun, Hye Ran
AU - Roh, Myung Cheol
AU - Kim, Kil Cheon
AU - Choi, Yeong Woo
AU - Lee, Seong Whan
PY - 2002
Y1 - 2002
N2 - Text extraction and recognition from still and moving images have many important applications. But, when a source image is an ordinary natural scene, text extraction becomes very complicated and difficult. In this paper, we suggest text extraction methods based on color and gray information. The method using the color image is processed by color reduction, color clustering, and text region extraction and verifications. The method using the gray-level image is processed by edge detection, long line removal, repetitive run-length smearing (RLS), and text region extraction and verifications. Combining two approaches improves the extraction accuracies both in simple and in complex images. Also, estimating skew and perspective of the extracted text regions are considered.
AB - Text extraction and recognition from still and moving images have many important applications. But, when a source image is an ordinary natural scene, text extraction becomes very complicated and difficult. In this paper, we suggest text extraction methods based on color and gray information. The method using the color image is processed by color reduction, color clustering, and text region extraction and verifications. The method using the gray-level image is processed by edge detection, long line removal, repetitive run-length smearing (RLS), and text region extraction and verifications. Combining two approaches improves the extraction accuracies both in simple and in complex images. Also, estimating skew and perspective of the extracted text regions are considered.
UR - http://www.scopus.com/inward/record.url?scp=84947803663&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84947803663&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84947803663
SN - 3540440682
SN - 9783540440680
VL - 2423
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 329
EP - 340
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PB - Springer Verlag
ER -