User-assisted ink-bleed reduction

IEEE Transactions on Image Processing

Volumn 19, Issue 10, 2010, Pages 2646-2658

  Huang, Yi ^a   Brown, Michael S ^b   Xu, Dong ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Document imaging processing; Dual layer markov random field (mrf); Ink bleed reduction

Indexed keywords

APPLICATION FRAMEWORKS; DATA COSTS; DOCUMENT IMAGING; DUAL LAYER; INTRA-LAYER; LABELED DATA; LIKELIHOOD ESTIMATION; MARKOV RANDOM FIELD; NEAREST NEIGHBORS; OLD MANUSCRIPTS; PARAMETER-TUNING; REDUCTION ALGORITHMS;

PIXELS; SECURITY OF DATA; STRUCTURAL FRAMES;

INK;

EID: 77956957589     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2010.2048971     Document Type: Article

References (26)

1. Y. Huang, M. Brown, and D. Xu, "A framework for reducing ink-bleed in old documents," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recogn., 2008, pp. 1-7.
2. Y. Huang and M. Brown, "User-assisted ink-bleed correction for handwritten documents," in Proc. IEEE/ACM Joint Conf. Digit. Libraries, 2008, pp. 263-271.
3. J. Bescos, "Image processing algorithms for readability enhancement of old manuscripts," Electron. Imag., vol. 1, pp. 392-397, 1989.
4. F. C. M. et al., "Toward on-line, worldwide access to vatican library materials," IBM J. Res. Devel., vol. 40, no. 2, pp. 139-162, Mar. 1996.
5. Z. Shi and V. Govindaraju, "Historical document image enhancement using background light intensity normalization," in Proc. Int. Conf. Pattern Recogn., 2004, pp. 473-476.
6. F. Drira, F. L. Bourgeois, and H. Emptoz, "Restoring ink bleed-through degraded document images using a recursive unsupervised classification technique," in Proc. Doc. Anal. Syst., 2006, pp. 38-49.
7. A. Tonazzini, L. Bedini, and E. Salerno, "Independent component analysis for document restoration," Int. J. Doc. Anal. Recogn., vol. 7, pp. 17-27, 2004.
8. C. Wolf, "Document ink bleed-through removal with two hidden Markov random fields and a single observation field," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 3, pp. 431-447, 2010.
9. G. Sharma, "Show-through cancellation in scans of duplex printed documents," IEEE Trans. Image Process., vol. 10, no. 5, pp. 736-754, May 2001.
10. A. Tonazzini, E. Salerno, and L. Bedini, "Fast correction of bleed-through distortion in grayscale documents by a blind source separation technique," Int. J. Doc. Anal. Recogn., vol. 10, pp. 17-27, 2007.
11. A. Tonazzini, L. Bedini, and E. Salerno, "A Markov model for blind image separation by a mean-field EM algorithm," IEEE Trans. Image Process., vol. 15, no. 2, pp. 473-482, Feb. 2006.
12. C. L. Tan, R. Cao, and P. Shen, "Restoration of archival documents using a wavelet technique," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 10, pp. 1399-1404, Oct. 2002.
13. Q. Wang, T. Xia, L. Li, and C. Tan, "Document image enhancement using directional wavelet," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recogn., 2003, pp. 534-539.
14. M. Brown and W. B. Seales, "Image restoration of arbitrarily warped document," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 10, pp. 1295-1306, Oct. 2004.
15. M. Brown and Y. Tsoi, "Geometric and shading correction of printed materials," IEEE Trans. Image Process., vol. 15, no. 6, Jun. 2006.
16. M. Pilu, "Undoing paper curl distortion using applicable surfaces," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recogn., 2001, pp. 67-72.
17. C. L. Tan, Z. Li, Z. Zhang, and T. Xia, "Restoring warped document images through 3-D shape modeling," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 2, pp. 195-208, Feb. 2006.
18. F. Bookstein, "Principal warps: Thin-plate splines and the decomposition of deformations," IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, no. 6, pp. 567-585, Jun. 1989.
19. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification. New York: Wiley-Interscience, 2000.
20. C. Chang and C. Lin, "LIBSVM: A library for support vector machines," 2001 [Online]. Available: http://www.csie.ntu.edu.tw/cjlin/ libsvm.
21. S. Li, Markov Random Field Modeling in Image Analysis, 2nd ed. New York: Springer-Verlag, 2001.
22. R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov, A. Agarwala, M. Tappen, and C. Rother, "Comparative study of energy minimization methods for Markov random fields," in Proc. Eur. Conf. Comput. Vis., 2006, pp. 16-29.
23. Y. Boykov and V. Kolmogorov, "An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 9, pp. 1124-1137, Sep. 2004.
24. Y. Boykov, O. Veksler, and R. Zabih, "Fast approximate energy minimization via graph cuts," IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 11, pp. 1222-1239, Nov. 2001.
25. V. Volmogorov and R. Zabih, "What energy functions can be minimized via graph cuts?," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 2, pp. 147-159, Feb. 2004.
26. C. J. van Rijsbergen, Information Retrieval. London, U.K.: Butterworth, 1979.