CFP last date
20 December 2024
Reseach Article

Automated Recognition of Text in Images: A Survey

by Kanika Wadhawan, E. Gajendran
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 127 - Number 15
Year of Publication: 2015
Authors: Kanika Wadhawan, E. Gajendran
10.5120/ijca2015906661

Kanika Wadhawan, E. Gajendran . Automated Recognition of Text in Images: A Survey. International Journal of Computer Applications. 127, 15 ( October 2015), 15-19. DOI=10.5120/ijca2015906661

@article{ 10.5120/ijca2015906661,
author = { Kanika Wadhawan, E. Gajendran },
title = { Automated Recognition of Text in Images: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 127 },
number = { 15 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 15-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume127/number15/22805-2015906661/ },
doi = { 10.5120/ijca2015906661 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:18:06.892788+05:30
%A Kanika Wadhawan
%A E. Gajendran
%T Automated Recognition of Text in Images: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 127
%N 15
%P 15-19
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

OCR (Optical Character Recognition) System works in the domain of Natural Language Processing and Image Processing. This is used to convert all the text information that is present in image form, to text format. Text is one of the most influential inventions of Humanity. The fertile and precise information incorporated in text is very useful in a wide range of applications that are computer-vision based, and hence text detection and recognition in natural scenes (e.g.: traffic sign boards, license plate, Hoardings and videos etc.) have become important and active research topics in computer vision and document analysis. This survey paper presents a review of various state-of-the-art techniques proposed for different processes (i.e. detection, localization, extraction, etc.) of text information processing in Images. Literature review can further serve as a good reference for researchers in the areas of scene text detection and recognition. The aim is to introduce the researchers to the latest trends in this area and to serve as a resource for developers who wish to integrate such solutions into their own work.

References
  1. Casey, R., Lecolinet, E.: A survey of methods and strategies in character segmentation. IEEE Trans. Pattern Anal. Mach. Intell.18 (7), 690–706 (2002)
  2. Chen, D., Odobez, J., Bourlard, H.: Text detection and recognition in images and video frames. Pattern Recogn.37 (3), 595–608 (2004)
  3. Chen, T., Ghosh, D., Ranganath, S. : Video-text extraction and recognition. In: IEEE Region 10 Conference, TENCON’04, vol.1, pp. 319–322 (2005)
  4. K. Jung, K. I. Kim, and Anil. K. Jain, “Text information extraction in images and video: a survey”, Pattern Recognition, vol. 37, 2004, pp.977-997.
  5. J. Zhang and R. Kasturi, “Extraction of Text Objects in Video Documents: Recent Progress”, DAS, 2008, pp.5-17.
  6. Yao C, Zhang X, Bai X, Liu W, Tu Z. Rotation-invariant features for multi-oriented text detection in natural images. PloS one, 2013, 8(8):e70173
  7. Yao C, Bai X, Shi B, LiuW. Strokelets: A learned multi-scale representation for scene text recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. 2014, 4042–4049
  8. Delakis, M., Garcia, C.: Text detection with convolutional neural networks. In: International Conference on Computer Vision Theory and Applications, vol. 2, pp. 290–294 (2008)
  9. ABBYY Fine Reader.http://finereader.abbyy.com/
  10. Microsoft Office Document Imaging. http://en.wikipe_dia.org/wiki/Microsoft_Office_Document_Imaging
  11. M. Cai, J. Song and M.R. Lyu, ”A New Approach for Video Text Detection,” in Proc. IEEE Int’l Conf. Image Processing, pp.117-120, 2002.
  12. Yao C, Bai X, Liu W, Ma Y, Tu Z. Detecting texts of arbitrary orientations in natural images. In: Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition. 2012, 1083–1090
  13. C. Jung, Q. Liu, and J. Kim, “A new approach for text segmentation using a stroke filter”, Signal Processing, vol.88, 2008, pp.1907-1916.
  14. X. Li, W. Wang, S. Jiang, Q. Huang, and Wen Gao, “Fast and Effective text detection”, ICIP, 2008, pp.969-972.
  15. C. Jung, Q. Liu, and J. Kim, “A stroke filter and its application to text localization”, Pattern Recognition Letters, vol.30, 2009, pp.114-122.
  16. B. Epshtien, E. Ofek, Y. Wexler, “Detecting text in natural scenes with Stroke Width Transform”, CVPR, 2010, pp. 2963 - 2970.
  17. P. Shiva kumara, W. Huang, C. L. Tan, “An Efficient Edge Based Technique for Text Detection in Video Frames”, DAS, 2008, pp.307-314.
  18. Hua, X., Yin, P., Zhang, H.: Efficient video text recognition using multiple frame integration. In: International Conference on Image Processing, vol. 2, pp. 397–400 (2002)
  19. Li, H., Doermann, D., Kia, O.: Automatic text detection and tracking in digital video. IEEE Trans. Image Process.9 (1), 147–156(2000)
  20. Yi C, Tian Y L. Text string detection from natural scenes by structure based partition and grouping. IEEE Transactions on Image Processing, 2011, 20(9): 2594–2605
  21. J. Park, G. Lee, E. Kim, J. Lim, S. Kim, H. Yang, M. Lee, and S.Hwang, “Automatic detection and recognition of Korean text in outdoor signboard Images”, Pattern Recognition Letters, vol.31,2010, pp.1728-1739.
  22. P. Shiva kumara, W. Huang, T. Q. Phan, C. L. Tan, “ Accurate videotext detection through classification of low and high contrast Images”, Pattern Recognition, vol.43, 2010, pp.2165-2185.
  23. P. Shiva kumara, A. Dutta, U. Pal, and C. L. Tan, “A New method for Handwritten scene text detection in video”, ICFHR, 2010, pp.387-392
  24. J. Yu and Y. Wang, “Apply SOM to Video Artificial text area detection”, Int. Conf. Internet computing for Science. And Engg.,2010, pp.137-141.
  25. X. Huang and H. Ma, “Automatic Detection and Localization of Natural scene text in Video”, ICPR, 2010, pp.3216-3219.
  26. Li H, Doermann D, Kia O. Automatic text detection and tracking in digital video. IEEE Transactions on Image Processing, 2000, 9(1):147–156
  27. M.R. Lyu, J. Song, and M. Cai, ”A Comprehensive Method for Multilingual Video Text Detection, Localization, and Extraction, ”IEEE Trans. Circuits System on Video Technology, vol. 15,no. 2, pp. 243-255, 2005.
  28. Yi, J., Peng, Y., Xiao, J.: Using multiple frame integration for the text recognition of video. In: International Conference on Document Analysis and Recognition, pp. 71–75 (2009)
  29. Yokobayashi, M., Wakahara, T.: Segmentation and recognition of characters in scene images using selective binarization in color space and GAT correlation. In: International Conference on Document Analysis and Recognition, pp. 167–171 (2005)
  30. Shivakumara P, Phan T Q, Tan C L. A laplacian approach to multioriented text detection in video. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(2): 412–419
  31. Z. Saidane and C. Gracia, “Automatic Scene Text Recognition using a Convolutional Neural Network”, CBDAR, 2007, pp.100-107.
  32. A. Ohkura, D. Deguchi, T. Takahashi, I. Ide, and H. Murasse, “Low resolution Character Recognition by Video-based Super-resolution”, ICDAR, 2009, pp.191-19.
  33. Z. Saidane, C. Garcia, and J. L. Dugelay, “The image Text Recognition Graph (iTRG)”, ICME, 2009, pp.266-269
  34. P. Shiva kumara, W. Huang and C.L. Tan, ”Efficient Video Text Detection using Edge Features,” in Proc. IEEE Int’l Conf. Pattern Recognition, pp. 1-4, 2008.
  35. Everingham M, Van Gool L, and Williams C K I, Winn J, Zisserman A. The pascal visual object classes (voc) challenge. International Journal of Computer Vision, 2010, 88(2): 303–338
  36. Z. Zhou, L. Li, C. L. Tan, “Edge based Binarization for video text images”, ICPR, 2010, pp.133-136.
  37. A. Mishra, K Alahari, and C. V. Jawahar, “An MRF Model for Binarization of Natural Scene Text”, ICDAR, 2011, pp-11-16.
  38. Toru Wakahara and Kohei Kita, “Binarization of Color Character Strings in Scene Images Using K-Means Clustering and Support Vector Machines”, ICDAR, 2011, pp.274-278.
  39. K. Ntirogiannis, B. Gatos, and I. Pratikakis “Binarization of Textual Content in Video Frames”, ICDAR, 2011, pp.673-677.
Index Terms

Computer Science
Information Sciences

Keywords

Text Detection Text Localization Text Recognition OCR