Journal of Information Processing Systems

  • 제11권4호
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  • Pages.528-537
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  • 2015
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Text Detection in Scene Images Based on Interest Points

  • 투고 : 2014.05.13
  • 심사 : 2015.04.14
  • 발행 : 2015.12.31
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초록

Text in images is one of the most important cues for understanding a scene. In this paper, we propose a novel approach based on interest points to localize text in natural scene images. The main ideas of this approach are as follows: first we used interest point detection techniques, which extract the corner points of characters and center points of edge connected components, to select candidate regions. Second, these candidate regions were verified by using tensor voting, which is capable of extracting perceptual structures from noisy data. Finally, area, orientation, and aspect ratio were used to filter out non-text regions. The proposed method was tested on the ICDAR 2003 dataset and images of wine labels. The experiment results show the validity of this approach.

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참고문헌

  1. K. Jung, K. I. Kim, and A. K. Jain, "Text Information extraction in images and video: a survey," Pattern Recognition, vol. 35, no. 5, pp. 977-997, 2004.
  2. P. Clark and M. Mirmehdi, "Recognising text in real scenes," International Journal of Document Analysis and Recognition, vol. 4, no. 4, pp. 243-257, 2002. https://doi.org/10.1007/s10032-001-0072-2
  3. B. K. Sin, S. K. Kim, and B. J. Cho, "Locating characters in scene images using frequency features," in Proceedings of 16th International Conference on Pattern Recognition, Quebec, Canada, 2002, pp. 489-492.
  4. D. Crandall, S. Antani, and R. Kasturi, "Extraction of special effects caption text events from digital video," International Journal of Document Analysis and Recognition, vol. 5, no. 2-3, pp. 138-157, 2003. https://doi.org/10.1007/s10032-002-0091-7
  5. Q. Ye, Q. Huang, W. Gao, and D. Zhao, "Fast and robust text detection in images and video frames," Image and Vision Computing, vol. 23, no. 6, pp. 565-576, 2005. https://doi.org/10.1016/j.imavis.2005.01.004
  6. J. Samarabandu and X. Liu, "An edge-based text region extraction algorithm for indoor mobile robot navigation," International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 1, no. 7, pp. 2008-2015, 2007.
  7. J. Gllavata, R. Ewerth, and B. Freisleben, "A robust algorithm for text detection in images," in Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis (ISPA2003), Rome, Italy, 2003, pp. 611-616.
  8. T. Nguyen, J. Park, and G. Lee, "Using 2D tensor voting in text detection," in Proceedings of 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), Dallas, TX, 2010, pp. 818-821.
  9. C. Tomasi and R. Manduchi, "Bilateral filtering for gray and color images," in Proceedings of 6th International Conference on Computer Vision (ICCV), Bombay, India, 1998, pp. 839-846.
  10. W. Forstner and E. Gulch, "A fast operator for detection and precise location of distinct point, corners and centres of circular features," in Proceedings of Intercommission Conference on Fast Processing of Photogrammetric Data, Interlaken, Switzerland, 1987, pp. 281-305.
  11. C. Schmid, R. Mohr, and C. Bauckhage, "Evaluation of interest point detectors," International Journal of Computer Vision, vol. 37, no. 2, pp. 151-172, 2000. https://doi.org/10.1023/A:1008199403446
  12. U. Kothe, "Integrated edge and junction detection with the boundary tensor," in Proceedings of 9th International Conference on Computer Vision, Nice, France, 2003, pp. 424-431.
  13. C. Harris and M. Stephens, "A combined corner and edge detector," in Proceedings of Alvey Vision Conference, Manchester, UK, 1988, pp. 147-151.
  14. G. Medioni, M. S. Lee, and C. K. Tang, A Computational Framework for Segmentation and Grouping. Amsterdam: Elsevier, 2000.
  15. W. S. Tong, C. K. Tang, and G. Medioni, "First order tensor voting, and application to 3-D scale analysis," in Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2001), Kauai, HI, 2001, pp. 175-182.
  16. ICDAR 2003 datasets, http://algoval.essex.ac.uk/icdar/Datasets.html.