References
[1]. Abid, A. (1997). 'Memory of the world': Preserving our documentary heritage. Museum International, 49(1), 40- 45. https://doi.org/10.1111/1468-0033.00074
[2]. Alahakoon, C. N. (2006). Identification of physical problems of major palm leaf manuscripts collections in Sri Lanka. Journal of the University Librarians Association of Sri Lanka, 10,54–66.
[3]. An, J., Kpeyiton, K. G., & Shi, Q. (2020). Grayscale images colorization with convolutional neural networks. Soft Computing, 24(7), 4751-4758. https://doi.org/10.1007/s00 500-020-04711-3
[4]. Arifin, A. Z., & Asano, A. (2006). Image segmentation by histogram thresholding using hierarchical cluster analysis. Pattern Recognition Letters, 27(13), 1515-1521. https://doi. org/10.1016/j.patrec.2006.02.022
[5]. Baird, H. S. (2003, August). Digital libraries and document image analysis. In Seventh International Conference on Document Analysis and Recognition (pp. 2-14). IEEE. https://doi.org/10.1109/ICDAR.2003.1227619
[6]. Bar, L., Brook, A., Sochen, N., &Kiryati, N. (2007). Deblurring of color images corrupted by impulsive noise. IEEE Transactions on Image Processing, 16(4), 1101-1111. https://doi.org/10.1109/TIP.2007.891805
[7]. Bar, L., Sochen, N., & Kiryati, N. (2005, April). Image deblurring in the presence of salt-and-pepper noise. In International Conference on Scale-Space Theories in Computer Vision (pp. 107-118). Heidelberg, Berlin: Springer. https://doi.org/10.1007/11408031_10
[8]. Bonny, M. Z., & Uddin, M. S. (2019, December). Degraded document enhancement through binarization techniques. In 2019, International Conference on Sustainable Technologies for Industry 4.0 (STI) (pp. 1-6). IEEE. https://doi.org/10.1109/STI47673.2019.9068099
[9]. Brown, M. S., & Seales, W. B. (2004). Image restoration of arbitrarily warped documents. IEEE Transactions on Pattern Analysis And Machine Intelligence, 26(10), 1295- 1306. https://doi.org/10.1109/TPAMI.2004.87
[10]. Chiu, Y. H., Chung, K. L., Yang, W. N., Huang, Y. H., & Liao, C. H. (2012). Parameter-free based two-stage method for binarizing degraded document images. Pattern Recognition, 45(12), 4250-4262. https://doi.org/ 10.1016/j.patcog.2012.02.023
[11]. Dey, S., Bhattacharya, B. B., Kundu, M. K., & Acharya, T. (2000, January). A fast algorithm for computing the Euler number of an image and its VLSI implementation. In Proceedings of 13th International Conference on VLSI Design (pp. 330-335). IEEE. https://doi.org/10.1109/ICVD. 2000.812628
[12]. Dobreva, M., & Ikonomov, N. (2004). Digital preservation and access to cultural and scientific heritage: Presentation of the KT-digicult-BG project. International Journal Information Theories & Applications, 11(3), 204–210.
[13]. Dubois, E., & Pathak, A. (2001, April). Reduction of bleed-through in scanned manuscript documents. In Paediatric Intensive Care Society, 1(4), 177-180.
[14]. Gatos, B., Pratikakis, I., & Perantonis, S. J. (2006). Adaptive degraded document image binarization. Pattern Recognition, 39(3), 317-327. https://doi.org/10. 1016/j.patcog.2005.09.010
[15]. Goltz, D., Attas, M., Young, G., Cloutis, E., & Bedynski, M. (2010). Assessing stains on historical documents using hyperspectral imaging. Journal of Cultural Heritage, 11(1), 19-26. https://doi.org/10.1016/j.culher.2009.11.003
[16]. Kavallieratou, E., & Antonopoulou, H. (2005). Advanced Concepts for Intelligent Vision Systems. Heidelberg, Berlin: Springer-Verlag.
[17]. Kim, S. J., Deng, F., & Brown, M. S. (2011). Visual enhancement of old documents with hyperspectral imaging. Pattern Recognition, 44(7), 1461-1469. https:// doi.org/10.1016/j.patcog.2010.12.019
[18]. Kong, X., Qian, Y., Jiao, G., & Miao, Z. (2020, April). Noise removing method for low-light-level image based on four-direction nonlocal means. In Sixth Symposium on Novel Optoelectronic Detection Technology and Applications (Vol. 11455, p. 114550T). International Society for Optics and Photonics. https://doi.org/10.1117/ 12.2559777
[19]. Kumar, D. U., Sreekumar, G., & Athvankar, U. (2009). Traditional writing system in southern India—palm leaf manuscripts. Design Thoughts, 7, 2-7.
[20]. Mello, C., Sanchez, A., Oliveira, A., & Lopes, A. (2008). An efficient gray-level thresholding algorithm for historic document images. Journal of Cultural Heritage, 9(2), 109-116. https://doi.org/10.1016/j.culher.2007.09.004
[21]. Montani, I., Sapin, E., Pahud, A., & Margot, P. (2012). Enhancement of writings on a damaged medieval manuscript using ultraviolet imaging. Journal of Cultural Heritage, 13(2), 226-228. https://doi.org/10.1016/j.culher. 2011.09.002
[22]. O'Gorman, L., Sammon, M. J., & Seul, M. (2008). Practical algorithms for image analysis with CD-ROM. New York, USA: Cambridge University Press.
[23]. Oh, H. H., Lim, K. T., & Chien, S. I. (2005). An improved binarization algorithm based on a water flow model for document image with inhomogeneous backgrounds. Pattern Recognition, 38(12), 2612-2625. https://doi.org/ 10.1016/j.patcog.2004.11.025
[24]. Quandt, A. B. (1996). Recent developments in the conservation of parchment manuscripts. The Book and Paper Group Annual, 15(199), 99-116.
[25]. Ramponi, G., Stanco, F., Dello Russo, W., Pelusi, S., & Mauro, P. (2005). Digital automated restoration of manuscripts and antique printed books. In Proceedings of Electronic Imaging and the VisualArts (pp.186–191).
[26]. Sahoo, J. (2004). Preservation of library materials: Some preventive measures. The Orissa Historical Research Journal, 47(1), 105-114.
[27]. Sauvola, J., & Pietikäinen, M. (2000). Adaptive document image binarization. Pattern Recognition, 33(2), 225-236. https://doi.org/10.1016/S0031-3203(99)00055-2
[28]. Saxena, L. P. (2014). An effective binarization method for readability improvement of stain-affected (degraded) palm leaf and other types of manuscripts. Current Science, 107(3), 489-496.
[29]. Saxena, L. P. (2018). Separation, classification and expert mapping of old grantha documents symbols. imanager's Journal on Pattern Recognition, 5(4), 51-67. https://doi.org/10.26634/jpr.5.4.16108
[30]. Saxena, L. P. (2019). A survey of manuscripts digitization to restoration using image processing. imanager's Journal on Pattern Recognition, 6(3), 27-36. https://doi.org/10.26634/jpr.6.3.17302
[31]. Saxena, L. P. (2019). Niblack's binarization method and its modifications to real-time applications: A review. Artificial Intelligence Review, 51(4), 673-705. https://doi. org/10.1007/s10462-017-9574-2
[32]. Saxena, L. P. (2020). A discussion on image binarization methods. i-manager's Journal on Image Processing, 7(4), 36-46. https://doi.org/10.26634/jip.7.4. 17331
[33]. Su, B., Lu, S., & Tan, C. L. (2010, June). Binarization of historical document images using the local maximum and minimum. In Proceedings of the 9th IAPR International Workshop on Document Analysis Systems (pp. 159-166). https://doi.org/10.1145/1815330.1815351
[34]. Surinta, O., & Chamchong, R. (2008, October). Image segmentation of historical handwriting from palm leaf manuscripts. In International Conference on Intelligent Information Processing (pp. 182-189). Boston, MA: Springer. https://doi.org/10.1007/978-0-387-87685-6_ 23
[35]. Thouin, P. D., & Chang, C. I. (2000). A method for restoration of low-resolution document images. International Journal on Document Analysis and Recognition, 2(4), 200-210. https://doi.org/10.1007/Pl0002 1526
[36]. Turner, N. (1994). The conservation of medieval manuscript illuminations and the question of compensation. WAAC Newsletter 16(1), 21–22.
[37]. Uhlí, Z. (2004). Manuscript digitization and electronic processing of manuscripts in the Czech national library. International Journal of Information Theories & Applications, 11(3), 257–262.
[38]. Wu, C. C., Chou, C. H., & Chang, F. (2008). A machine-learning approach for analyzing document layout structures with two reading orders. Pattern Recognition, 41(10), 3200-3213. https://doi.org/10.1016/ j.patcog.2008.03.014
[39]. Zhang, Z., & Tan, C. L. (2001, October). Restoration of images scanned from thick bound documents. In Proceedings 2001 International Conference on Image Processing (Cat. No. 01CH37205) (Vol. 1, pp. 1074-1077). IEEE. https://doi.org/10.1109/ICIP.2001.959235
