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Reseach Article

Automatic Detection and Inpainting of Text Images

by S. Bhuvaneswari, T. S. Subashini
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 61 - Number 7
Year of Publication: 2013
Authors: S. Bhuvaneswari, T. S. Subashini
10.5120/9941-4578

S. Bhuvaneswari, T. S. Subashini . Automatic Detection and Inpainting of Text Images. International Journal of Computer Applications. 61, 7 ( January 2013), 30-34. DOI=10.5120/9941-4578

@article{ 10.5120/9941-4578,
author = { S. Bhuvaneswari, T. S. Subashini },
title = { Automatic Detection and Inpainting of Text Images },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 61 },
number = { 7 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 30-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume61/number7/9941-4578/ },
doi = { 10.5120/9941-4578 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:08:29.045252+05:30
%A S. Bhuvaneswari
%A T. S. Subashini
%T Automatic Detection and Inpainting of Text Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 61
%N 7
%P 30-34
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The proposed system detects text using connect component labelling and a set of selection/ rejection criteria which helps to retain the text region alone. The detected text region is then inpainted using fast marching algorithm which uses the pixel information that is present in the non-text region of the image for inpainting the detected text region. This work is done in two steps. The first step detects the text region from the image without the user manually marking it and in the second step the text is de-occluded from the image using the existing fast marching inpainting algorithm.

References
  1. R. C. Gonzalaz and Redwoods, Digital Image Processing, 2nd ed. , Pearson Education, 2002.
  2. A. Criminisi, P. Perez, K. Toyama, "Region Filling and object removal by exemplar based image inpainting", IEEE transactions on image processing, Vol. 13, No. 9, pp. 1-7, 2004.
  3. S. Bhuvaneshwari, T. S. Subashini, S. Soundharya, V. Ramalingam "A novel and fast exemplar based approach for filling portions in an image", IEEE Proceedings on the International conference on recent trends in information technology (ICRTIT), pp. 91-96, 2012.
  4. D. L. Smith, J. Field, and E. G. Learned-Miller, " Enforcing similarity constraints with integer programming for better scene text recognition" , CVPR, pp. 73-80, 2011.
  5. J. J. Weinman, E. G. Learned-Miller, and A. R. Hanson, "Scene text recognition using similarity and a lexicon with sparse belief propagation", PAMI, pp. 1-11, 2009.
  6. J. Sushma, M. Padmaja, "Text Detection in color images", IEEE Proceedings on the International conference on intelligent agent & multi agent systems (IAMA), pp. 1-6, 2009.
  7. Nobuo Ezaki, Marius Bulacu, Lambert Schomaker, "Text Detection from Natural Scene Images: Towards a System for Visually Impaired Persons", IEEE Proceedings on the 17th International conference on ICPR, pp. 683-686, 2004.
  8. J. Ohya,A. Shio,S. Akamatsu, "Recognizing Characters in Scene Images", IEEE transactions on PAMI, Vol. 16, No. 2, pp. 214-224, 1994.
  9. RodolfoP. DosSantos, S. Gabriela, Clemente, TsangIng Ren, George D. C. Calvalcanti, "Text Line segmentation based on morphology and histogram projection", IEEE Proceedings on the 10th International conference on document analysis and recognition (ICDAR), pp. 651-655, 2009.
  10. Mariella Dimiccoli, Philippe Salembier, "Perceptual filtering with connected operators and image inpainting", ISMM Proceedings on the 8th International symposium on mathematical morphology, pp. 227-238, 2007.
  11. Muthukumar. S, Dr. Krishnan. N, Pasupathi. P. Deepa. S, " Analysis of Image Inpainting techniques with Exemplar, Poisson, Successive Elimination and 8 pixel Neighborhood methods", International Journal of Computer Applications(0975 – 8887), Vol. 9, November 2010.
  12. Faouzi Benzarti, Hamid Amiri, "Repairing and Inpainting Damaged Images using Diffusion Tensor", International Journal of Computer Science (IJCSI), Vol. 9, July 2012.
  13. M. J. Fadiii,J. LStarck and F. Murtagh, "Inpainting and Zooming using sparse Representation", The Computer Journal, pp. 64-79, 2007.
  14. Qixiang Ye, Wen Gao, Wiquiang Wang, WeiZeng, "A robust text detection algorithm in images and video frame", IEEE Proceedings on the International conference on information, communication and signal processing (ICICS), Vol. 2, pp. 930-932, 2012.
  15. Khurram Khurshd, Imran Siddiqi, Claudie Faure, Nicole Vincent, "Comparison of Niblack inspired Binarization methods for ancient documents", SPIE-ISAT proceedings on the International conference on Document Recognition and Retrieval, 2009.
  16. Celine Thillou, Silvio Ferreira, Bernard Gosselin, "An Embedded Application for Degraded Text Recognition", Vol. 13, pp. 2127-2135, 2005.
  17. Manjusha. K, Sachin Kumar. S, Jolly Rajendran, K. P. Soman, "Hindi Character Segmentation in Document Images using Level set methods and Non-linear Diffusion", International Journal of Computer Applications(IJCA), Vol. 44-No. 16, April 2012.
  18. Khaoula Elagouni, Christopic Garcia, Franck Mamalet, Pascale Sebillot , "Combining Multiscale Character Recognition and Linguistic Knowledge for natural Scene Text OCR", IAPR International Workshop on Document Analysis Systems, pp. 120-124, 2012.
  19. Graham Leedham, Chen Yan Kalyan Takru, Joie Hadi Nata Tan and Li Mian, "Comparison of Some Thresholding algorithms for text/Background Segmentation in difficult document images", IEEE Proceedings on the Seventh international Conference on Document Analysis and Recognition (ICDAR), pp. 859-864, 2003.
  20. Alexandru Telea, "An image Inpainting Technique Based on the Fast Marching Algorithm", Journal of Graphics tools, Vol. 9, No. 1, pp. 25-38, 2004.
Index Terms

Computer Science
Information Sciences

Keywords

Niblack's algorithm CCL selection criteria inpainting mask fast marching algorithm