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A Hybrid Image Restoration Algorithm for Digitized Degraded Historical Documents
Abstract
The historical documents have quite importance in our life because historical documents hold the important information about the old civilizations. However, because of many factors these documents are found in degraded form. Historical documents contain important information so we need to restore them. There are hundreds of thousands historical documents are available. If these documents are restored manually then it is a time consuming task. Now days, the historical documents are stored in the computer memories in the form of digital historical documents. The digitized historical documents are easy to restore than the manual restoration process on the historical documents. In this paper, the hybrid method is used to restore the historical documents. The proposed algorithm is capable of restoring most of the digitized historical documents accurately. This algorithm is capable of removing the most of the noises and spots from the digitized historical documents. This algorithm is the hybridization of morphological operations, image de-noising filters (wiener filter [10], median filter, etc), image dilation, OTSU thresholding, and Sauvola thresholding techniques. The normalized absolute error (NAE), Mean Square Error (MSE), and peak signal to noise ratio (PSNR) is taken as the performance parameters. The performance of the proposed algorithm is based on these parameters is better and the results are higher than the existing algorithms, when compared.
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References
Akihito Kitadai, M. Nakagawa, H. Baba, and A. Watanabe, “Similarity evaluation and shape feature extraction for character pattern retrieval to support reading historical documents”, in Proc. IAPR Intl. WDAS, pp. 359–363, 2012.
B. Gangamma and Srikanta Murthy K, "Enhancement of Degraded Historical Kannada Documents", International Journal of Computer Applications, Vol. 29, No.11, pp. 1-6, 2011.
B. Gangamma, Srikanta Murthy K, and Arun Vikas Singh," Restoration of Degraded Historical Document Image", Journal of Emerging Trends in Computing and Information Sciences, Vol. 3, No. 5, pp. 792-798, 2012.
B. Gatos, I. Pratikakis, and S. J. Perantonis, “Adaptive degraded document image binarization”, Elsevier Trans. Pattern Recogn., Vol. 39, No. 3, pp. 317–327, 2006.
C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images”, in Proc. IEEE ICCV, pp. 839–846, 1998.
Chen Yan, and Graham Leedham," The Multistage Approach to Information Extraction in Degraded Document Images", IEEE, pp. 2128-2132, 2004.
D. Tschumperl´e and R. Deriche, “Vector-valued image regularization with PDE’s: A common framework for different applications”, IEEE Trans. PAMI, Vol. 27, No. 4, pp. 506–517, 2005.
Extrapolation, interpolation, and smoothing stationary time series. New York: Wiley, 1949.
Fadoua Drira, Frank LeBourgeois, and Hubert Emptoz," A New PDE-based Approach for Singularity-Preserving Regularization: Application to Degraded Characters Restoration", International Journal of Document Analysis and Recognition, pp. 6-42, 2010.
Hiroko Furuya and Shintaro Eda, Testuya Shimamura," Image Restoration via Wiener Filteringin the Frequency Domain", Wseas Transactions On Signal Processing, Issue 2, Vol. 5, pp. 63-73, February 2009.
K. Shirani Y. Endo, A. Kitadai, S. Inoue, and N. Kurushima, “Character Shape Restoration of Binarized Historical Documents by Smoothing via Geodesic Morphology”, ICDAR, Vol. 12, pp. 1285-1289, 2013.
Krisda Khankasikam, " Restoration of Degraded Historical Document Image: An Adaptive Multilayer-Information Binarization Technique", Journal of Information Science and Engineering, pp. 209-227, 2013.
Kusum Grewal and Renu Malhan, "Design Of Morphological Approach To Detect And Eliminate Ink Bleed In Document Images", IJREAS, Issue 2, Vol. 2, pp. 137-145, 2012.
L. Xu, Q. Yan, Y. Xia, and J. Jia, “Structure extraction from texture via relative total variation”, ACM TOG (Proc. SIGGRAPH Asia), Vol. 31, No. 6, pp. 139:1–139:10, 2012.
M. R. Gupta, N. P. Jacobson, and E. K. Garcia, “Ocr binarization and image pre-processing for searching historical documents”, Elsevier Trans. Pattern Recogn., Vol. 40, No. 2, pp. 389–397, 2007.
Md. Iqbal Quraishi, Mallika De, Krishna Gopal Dhal, Saheb Mondal, and Goutam Das, “A Novel Hybrid Approach To Restore Historical Degraded Documents”, ISSP, Vol. 1, pp. 185-189, 2013.
Ms. Ketki R. Ingole and Prof. V K. Shandilya, " Image Restoration of Historical Manuscripts", International Journal of Computer Science & Engineering Technolo, Vol. 2, No. 4, pp. 102-107.
Ntogas, Nikolaos and Ventzas, Dimitrios, "A Binarization Algorithm for Historical Manuscripts", International Conference on Communications, pp. 41-51, 2008.
Pradeepa D. Samarasinghe, and Rodney A. Kennedy, "Minimum Kurtosis CMA Deconvolution for Blind Image Restoration", IEEE, pp. 271-276, 2008.
R. F. Moghaddam, D. R.-H´enault, and M. Cheriet, “Restoration and segmentation of highly degraded characters using a shape-independent level set approach and multi-level classifiers”, in Proc. IAPR ICDAR, pp. 828–832, 2009.
Rachel Mabanag Chong and Toshihisa Tanaka, "Motion Blur Identification Using Maxima Locations for Blind Colour Image Restoration", Future Technology Research Association International, Vol. 1, No. 1, pp. 49-56, December 2010.
Sandhya N, R. Krishnan and D. R. Ramesh Babu, "A language independent Characterization of Document Image Noise in Historical Scripts", International Journal of Computer Applications, Vol. 50, No. 9, pp. 11-18, 2012.
Savita Borole, Minal Thobde, Reshma Hore, and Shraddha Shinde, "Text Extraction Using Adaptive Thresholding", International Journal of Computer Science and Information Technologies, Vol. 5, No 2, pp. 1759-1763, 2014.
Tony F. Chan, Ke Chen, And Jamylle L. Cart," Iterative Methods For Solving The Dual Formulation Arising From Image Restoration", Electronic Transactions on Numerical Analysis, Vol. 26, pp. 299-311, 2007.
Weisheng Dong, Lei Zhang, Guangming Shi, and Xin Li, "Nonlocally Centralized Sparse Representation for Image Restoration", IEEE Transactions On Image Processing, Vol. 22, No. 4, pp. 1620, April 2013.
Y. Chen and G. Leedham, "Decompose algorithm for thresholding degraded historical document images", IEE Proc.-Vis. Image Signal Process., Vol. 152, No. 6, pp. 702-714, December 2005.
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