Scene text extraction in natural scene images using hierarchical feature combining and verification

K. C. Kim; H. R. Byun; Y. J. Song; Y. W. Choi; S. Y. Chi; K. K. Kim; Y. K. Chung

doi:10.1109/ICPR.2004.1334350

Scene text extraction in natural scene images using hierarchical feature combining and verification

K. C. Kim, H. R. Byun, Y. J. Song, Y. W. Choi, S. Y. Chi, K. K. Kim, Y. K. Chung

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

77 Citations (Scopus)

Abstract

We propose a method that extracts text regions in natural scene images using low-level image features and that verifies the extracted regions through a high-level text stroke feature. Then the two level features are combined hierarchically. The low-level features are color continuity, gray-level variation and color variance. The color continuity is used since most of the characters in a text region have the same color, and the gray-level variation is used since the text strokes are distinctive to the background in their gray-level values. Also, the color variance is used since the text strokes are distinctive in their colors to the background, and this value is more sensitive than the gray-level variations. As a high level feature, text stroke is examined using multi-resolution wavelet transforms on local image areas and the feature vector is input to a SVM(Support Vector Machine) for verification. We tested the proposed method with various kinds of the natural scene images and confirmed that extraction rates are high even in complex images.

Original language	English
Title of host publication	Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
Editors	J. Kittler, M. Petrou, M. Nixon
Pages	679-682
Number of pages	4
DOIs	https://doi.org/10.1109/ICPR.2004.1334350
Publication status	Published - 2004
Event	Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom Duration: 2004 Aug 23 → 2004 Aug 26

Publication series

Name	Proceedings - International Conference on Pattern Recognition
Volume	2
ISSN (Print)	1051-4651

Other

Other	Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
Country/Territory	United Kingdom
City	Cambridge
Period	04/8/23 → 04/8/26

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition

Access to Document

10.1109/ICPR.2004.1334350

Cite this

Kim, K. C., Byun, H. R., Song, Y. J., Choi, Y. W., Chi, S. Y., Kim, K. K., & Chung, Y. K. (2004). Scene text extraction in natural scene images using hierarchical feature combining and verification. In J. Kittler, M. Petrou, & M. Nixon (Eds.), Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 (pp. 679-682). (Proceedings - International Conference on Pattern Recognition; Vol. 2). https://doi.org/10.1109/ICPR.2004.1334350

@inproceedings{d930ef1997e64bb3bf8fb63dd079b218,

title = "Scene text extraction in natural scene images using hierarchical feature combining and verification",

abstract = "We propose a method that extracts text regions in natural scene images using low-level image features and that verifies the extracted regions through a high-level text stroke feature. Then the two level features are combined hierarchically. The low-level features are color continuity, gray-level variation and color variance. The color continuity is used since most of the characters in a text region have the same color, and the gray-level variation is used since the text strokes are distinctive to the background in their gray-level values. Also, the color variance is used since the text strokes are distinctive in their colors to the background, and this value is more sensitive than the gray-level variations. As a high level feature, text stroke is examined using multi-resolution wavelet transforms on local image areas and the feature vector is input to a SVM(Support Vector Machine) for verification. We tested the proposed method with various kinds of the natural scene images and confirmed that extraction rates are high even in complex images.",

author = "Kim, {K. C.} and Byun, {H. R.} and Song, {Y. J.} and Choi, {Y. W.} and Chi, {S. Y.} and Kim, {K. K.} and Chung, {Y. K.}",

year = "2004",

doi = "10.1109/ICPR.2004.1334350",

language = "English",

isbn = "0769521282",

series = "Proceedings - International Conference on Pattern Recognition",

pages = "679--682",

editor = "J. Kittler and M. Petrou and M. Nixon",

booktitle = "Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004",

note = "Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 ; Conference date: 23-08-2004 Through 26-08-2004",

}

Kim, KC, Byun, HR, Song, YJ, Choi, YW, Chi, SY, Kim, KK & Chung, YK 2004, Scene text extraction in natural scene images using hierarchical feature combining and verification. in J Kittler, M Petrou & M Nixon (eds), Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004. Proceedings - International Conference on Pattern Recognition, vol. 2, pp. 679-682, Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, United Kingdom, 04/8/23. https://doi.org/10.1109/ICPR.2004.1334350

Scene text extraction in natural scene images using hierarchical feature combining and verification. / Kim, K. C.; Byun, H. R.; Song, Y. J. et al.

Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004. ed. / J. Kittler; M. Petrou; M. Nixon. 2004. p. 679-682 (Proceedings - International Conference on Pattern Recognition; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - We propose a method that extracts text regions in natural scene images using low-level image features and that verifies the extracted regions through a high-level text stroke feature. Then the two level features are combined hierarchically. The low-level features are color continuity, gray-level variation and color variance. The color continuity is used since most of the characters in a text region have the same color, and the gray-level variation is used since the text strokes are distinctive to the background in their gray-level values. Also, the color variance is used since the text strokes are distinctive in their colors to the background, and this value is more sensitive than the gray-level variations. As a high level feature, text stroke is examined using multi-resolution wavelet transforms on local image areas and the feature vector is input to a SVM(Support Vector Machine) for verification. We tested the proposed method with various kinds of the natural scene images and confirmed that extraction rates are high even in complex images.

AB - We propose a method that extracts text regions in natural scene images using low-level image features and that verifies the extracted regions through a high-level text stroke feature. Then the two level features are combined hierarchically. The low-level features are color continuity, gray-level variation and color variance. The color continuity is used since most of the characters in a text region have the same color, and the gray-level variation is used since the text strokes are distinctive to the background in their gray-level values. Also, the color variance is used since the text strokes are distinctive in their colors to the background, and this value is more sensitive than the gray-level variations. As a high level feature, text stroke is examined using multi-resolution wavelet transforms on local image areas and the feature vector is input to a SVM(Support Vector Machine) for verification. We tested the proposed method with various kinds of the natural scene images and confirmed that extraction rates are high even in complex images.

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Kim KC, Byun HR, Song YJ, Choi YW, Chi SY, Kim KK et al. Scene text extraction in natural scene images using hierarchical feature combining and verification. In Kittler J, Petrou M, Nixon M, editors, Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004. 2004. p. 679-682. (Proceedings - International Conference on Pattern Recognition). doi: 10.1109/ICPR.2004.1334350

Scene text extraction in natural scene images using hierarchical feature combining and verification

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