CFP last date
22 July 2024
Reseach Article

Study on Soft Edge Transition Correction using Multilayer MRC Model

Published on December 2013 by Umesh P. Akare, N. G. Bawane
National Conference on Innovative Paradigms in Engineering & Technology 2013
Foundation of Computer Science USA
NCIPET2013 - Number 7
December 2013
Authors: Umesh P. Akare, N. G. Bawane
e55d83aa-c22b-4d16-8a99-938d7eb75c4f

Umesh P. Akare, N. G. Bawane . Study on Soft Edge Transition Correction using Multilayer MRC Model. National Conference on Innovative Paradigms in Engineering & Technology 2013. NCIPET2013, 7 (December 2013), 14-18.

@article{
author = { Umesh P. Akare, N. G. Bawane },
title = { Study on Soft Edge Transition Correction using Multilayer MRC Model },
journal = { National Conference on Innovative Paradigms in Engineering & Technology 2013 },
issue_date = { December 2013 },
volume = { NCIPET2013 },
number = { 7 },
month = { December },
year = { 2013 },
issn = 0975-8887,
pages = { 14-18 },
numpages = 5,
url = { /proceedings/ncipet2013/number7/14741-1425/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Innovative Paradigms in Engineering & Technology 2013
%A Umesh P. Akare
%A N. G. Bawane
%T Study on Soft Edge Transition Correction using Multilayer MRC Model
%J National Conference on Innovative Paradigms in Engineering & Technology 2013
%@ 0975-8887
%V NCIPET2013
%N 7
%P 14-18
%D 2013
%I International Journal of Computer Applications
Abstract

The mixed raster content (MRC) image represents a compound image which is a superposition of layers. This image model is very efficient for representing sharp text and graphics onto a background. In this binary mask layer is used. The problem occurs when one deals with scanned data and soft edges. These edges are neither shown as a background nor as a foreground. To detect segmented soft edges and a method to correct and sharpen the image within the MRC model is highly required. This paper presents details on this aspect while discussing preprocessing of the compound images with the MRC standard model.

References
  1. de Queiroz, R. L. , Fan, Z. , Tran, T. D. , 2000, Optimizing block-thresholding segmentation for multilayer compression of compound images. IEEE Trans. Image Proc. 9(9), 1461–1471
  2. Ricardo L. de Queiroz,Oct. 1999, Compression of Compound Documents. Proc. IEEE international Conference on Image Processing, ICIP, Kobe, Japan, 25PS1. 1.
  3. Feng, G. , Bouman, C. A. , 2006, High-quality mrc document coding. IEEE Trans. Image Proc. 15(10), 3152–3169
  4. de Queiroz, R. , Buckley, R. , Xu, M. , 2000, Mixed raster content (MRC) model for compound image compression. In: Proceedings images. IEEE Trans. Image Proc. 9(9), 1461–1471.
  5. Lam, E. Y. ,2004, Compound document compression with model-based biased reconstruction. J. Electron. Imaging 13(1), 191–194
  6. Bottou, L. , Haffner, P. , Howard, P. G. , Simard, P. , Bengio, Y. , LeCun, Y. ,1998, High quality document image compression with DjVu. J. Elec. Imaging 7(3), 410–425
  7. Ricardo L. de Queiroz, 2006, Pre-Processing for MRC Layers of Scanned Images. ICIP ,pp-3093-3096
  8. Eri Haneda, Charles A. Bouman, June 2011, Text Segmentation for MRC Document Compression. IEEE Transactions on Image Processing, Vol. 20, No. 6.
  9. Barthel, K. U. , Partlin, S. M. , Thierschmann, M. , 2000, New technology for raster document image compression. In: Part of the IS&T/SPIE Conference on Document Recognition and Retrieval VII, San Jose, CA, vol. 3967, pp. 286–290
  10. Thierschmann, M. , Barthel, K. U. , Martin, U. -E. , 2001, A scalable DSP architecture for high-speed color document compression. In: Kantor, P. B. , Lopresti, D. P. , Zhou, J. (eds. ) Document Recognition and Retrieval VIII. Proceedings of SPIE, vol. 4307, pp. 158–166
  11. Wu, B. -F. , Chiu, C. -C. , Chen, Y. -L. ,2004, Algorithms for compressing compound document images with large text/background overlap. IEE Proc. Vis. Image Signal Process. 151(6), 453–459
  12. Haneda, E. , Yi, J. , Bouman, C. A. , 2007, Segmentation for MRC compression. In: Eschbach, R. , Marcu G. G. (eds. ) Color Imaging XII: Processing, Hardcopy, and Applications. Proceedings of SPIEIS&T Electronic Imaging, vol. 6493, pp. 252–262
  13. Sarfraz, M. , Zidouri, A. , Nawaz, S. N. ,2005, On Offline arabic character recognition. In: Sarfraz M. (ed. ) Computer-Aided Intelligent Recodgnition: Techniques and Applications. Wiley, NY
  14. Fan, Z. , Jacobs, T. ,2005, Segmentation for mixed raster contents with multiple extracted constant color areas. Proc. SPIE-IS&T Electron. Imaging 5667, 251–262
  15. Zaghetto, A. , de Queiroz, R. L. ,2008, Iterative pre and post processing for MRC layers of scanned documents. In: Proceedings of IEEE International Conference on Image Processing, ICIP, San Diego, CA, USA, Oct.
  16. R. L. de Queiroz, D. Mukherjee, 2008, MRC Compression of Compound Documents Using Threshold Segmentation, Iterative Data-filling and H. 264/AVC-INTRA. Sixth Indian Conference on Computer Vision, Graphics & Image Processing, ICVGIP.
  17. Sezgin, M. , Sankur, B. ,2004, Survey over image thresholding techniques and quantitative performance evaluation. J. Elec. Imaging 13(1), 146–165
  18. Haneda, E. , Yi, J. , Bouman, C. A. ,2007, Segmentation for MRC compression. In: Eschbach, R. , Marcu G. G. (eds. ) Color Imaging XII: Processing, Hardcopy, and Applications. Proceedings of SPIEIS&T Electronic Imaging, vol. 6493, pp. 252–262
  19. Trier, O. D. , Taxt, T. ,1995, Evaluation of binarization methods for document images. IEEE Trans. Pattern Anal. Mach. Intell. PAMI 17(3), 312–315
  20. Ascher, R. N. , Nagy, G. , 1974, A means for achieving a high degree of compaction on scan-digitized printed text. IEEE Trans. Comput. 23, 1174–1179
  21. R. L. de Queiroz, 2005 Compressing Compound Documents, in The Document and Image Compression Handbook, edited by M. Barni,Marcel-Dekkar,
  22. Patrice Y. Simard, Henrique S. Malvar, James Rinker, and Erin Renshaw,2004, A Foreground/Background Separation Algorithm for Image Compression, Proceedings of the Data Compression Conference (DCC'04)
  23. Ronald H. Y. Chung, Nelson H. C. Yung, Paul Y. S. Cheung, 2005, An Efficient Parameterless Quadrilateral-Based Image Segmentation Method, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 27, No. 9,pp-1446-1458
  24. Alexandre Zaghetto, Ricardo L. de Queiroz, 2008, Iterative Pre- and Post-Processing for MRC Layers of Scanned Documents. ICIP. pp-1009-1012
  25. Barthel, K. U. , Partlin, S. M. , Thierschmann, M. , 2000, New technology for raster document image compression. In: Part of the IS&T/SPIE Conference on Document Recognition and Retrieval VII, San Jose, CA, vol. 3967, pp. 286–290
  26. Hadi Grailu • Mojtaba Lotfizad • Hadi Sadoghi-Yazdi, 2009, Farsi and Arabic document images lossy compression based on the mixed raster content model , IJDAR 12:227–248
Index Terms

Computer Science
Information Sciences

Keywords

Mixed Raster Content (mrc) Model Preprocessing Segmentation Edge Transition