Text extraction in digital news video using morphology

Hyeran Byun, Inyoung Jang, Yeongwoo Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, a new method is presented to extract both superimposed and embedded scene texts in digital news videos. The algorithm is summarized in the following three steps: preprocessing, extracting candidate regions, and filtering candidate regions. For the first preprocessing step, a color image is converted into a gray-level image and a modified local adaptive thresholding is applied to the contrast-stretched image. In the second step, various morphological operations and Geo-correction method are applied to remove non-text components while retaining the text components. In the third filtering step, non-text components are removed based on the characteristics of each candidate component such as the number of pixels and the bounding box of each connected component Acceptable results have been obtained using the proposed method on 300 domestic news images with a recognition rate of 93.6%. Also, the proposed method gives good performance on the various kinds of images such as foreign news and film videos.

Original languageEnglish
Title of host publicationDocument Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings
PublisherSpringer Verlag
Pages341-352
Number of pages12
ISBN (Print)3540440682, 9783540440680
Publication statusPublished - 2002 Jan 1
Event5th International Workshop on Document Analysis Systems, DAS 2002 - Princeton, United States
Duration: 2002 Aug 192002 Aug 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2423
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Workshop on Document Analysis Systems, DAS 2002
CountryUnited States
CityPrinceton
Period02/8/1902/8/21

Fingerprint

Digital Video
Preprocessing
Filtering
Pixels
Adaptive Thresholding
Color
Morphological Operations
Color Image
Connected Components
Pixel
Text

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Byun, H., Jang, I., & Choi, Y. (2002). Text extraction in digital news video using morphology. In Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings (pp. 341-352). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2423). Springer Verlag.
Byun, Hyeran ; Jang, Inyoung ; Choi, Yeongwoo. / Text extraction in digital news video using morphology. Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings. Springer Verlag, 2002. pp. 341-352 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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abstract = "In this paper, a new method is presented to extract both superimposed and embedded scene texts in digital news videos. The algorithm is summarized in the following three steps: preprocessing, extracting candidate regions, and filtering candidate regions. For the first preprocessing step, a color image is converted into a gray-level image and a modified local adaptive thresholding is applied to the contrast-stretched image. In the second step, various morphological operations and Geo-correction method are applied to remove non-text components while retaining the text components. In the third filtering step, non-text components are removed based on the characteristics of each candidate component such as the number of pixels and the bounding box of each connected component Acceptable results have been obtained using the proposed method on 300 domestic news images with a recognition rate of 93.6{\%}. Also, the proposed method gives good performance on the various kinds of images such as foreign news and film videos.",
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Byun, H, Jang, I & Choi, Y 2002, Text extraction in digital news video using morphology. in Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2423, Springer Verlag, pp. 341-352, 5th International Workshop on Document Analysis Systems, DAS 2002, Princeton, United States, 02/8/19.

Text extraction in digital news video using morphology. / Byun, Hyeran; Jang, Inyoung; Choi, Yeongwoo.

Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings. Springer Verlag, 2002. p. 341-352 (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 proceedingConference contribution

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N2 - In this paper, a new method is presented to extract both superimposed and embedded scene texts in digital news videos. The algorithm is summarized in the following three steps: preprocessing, extracting candidate regions, and filtering candidate regions. For the first preprocessing step, a color image is converted into a gray-level image and a modified local adaptive thresholding is applied to the contrast-stretched image. In the second step, various morphological operations and Geo-correction method are applied to remove non-text components while retaining the text components. In the third filtering step, non-text components are removed based on the characteristics of each candidate component such as the number of pixels and the bounding box of each connected component Acceptable results have been obtained using the proposed method on 300 domestic news images with a recognition rate of 93.6%. Also, the proposed method gives good performance on the various kinds of images such as foreign news and film videos.

AB - In this paper, a new method is presented to extract both superimposed and embedded scene texts in digital news videos. The algorithm is summarized in the following three steps: preprocessing, extracting candidate regions, and filtering candidate regions. For the first preprocessing step, a color image is converted into a gray-level image and a modified local adaptive thresholding is applied to the contrast-stretched image. In the second step, various morphological operations and Geo-correction method are applied to remove non-text components while retaining the text components. In the third filtering step, non-text components are removed based on the characteristics of each candidate component such as the number of pixels and the bounding box of each connected component Acceptable results have been obtained using the proposed method on 300 domestic news images with a recognition rate of 93.6%. Also, the proposed method gives good performance on the various kinds of images such as foreign news and film videos.

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Byun H, Jang I, Choi Y. Text extraction in digital news video using morphology. In Document Analysis Systems V - 5th International Workshop, DAS 2002, Proceedings. Springer Verlag. 2002. p. 341-352. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).