Abstract
In this paper we present a recursive algorithm for the cleaning and the enhancing of historical documents. Most of the algorithms, used to clean and enhance documents or transform them to binary images, implement combinations of complicated image processing techniques which increase the computational cost and complexity. Our algorithm simplifies the procedure by taking into account special characteristics of the document images. Moreover, the fact that the algorithm consists of iterated steps, makes it more flexible concerning the needs of the user. At the experimental results, comparison with other methods is provided.
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Bernsen, J.: Dynamic thresholding of grey-level images. In: Proc. 8th International Conference on Pattern Recognition (ICPR8), Paris, France, October 1986, pp. 1251–1255 (1986)
Gatos, B., Pratikakis, I., Perantonis, S.J.: An adaptive binarisation technique for low quality historical documents. In: Marinai, S., Dengel, A.R. (eds.) DAS 2004. LNCS, vol. 3163, pp. 102–113. Springer, Heidelberg (2004)
Leedham, G., Varma, S., Patankar, A., Govindaraju, V.: Separating Text and Background in Degraded Document Images - A Comparison of Global Thresholding Techniques for Multi-Stage Thresholding. In: Proceedings Eighth InternationalWorkshop on Frontiers of Handwriting Recognition, September 2002, pp. 244–249 (2002)
Leydier, Y., LeBourgeois, F., Emptoz, H.: Serialized Unsupervised Classifier for Adaptative Color Image Segmentation: Application to Digitized Ancient Manuscripts. In: ICPR, Cambridge, 23-26, pp. 494–497 (2004)
Niblack, W.: An Introduction to Digital image processing, pp. 115–116. Prentice-Hall, Englewood Cliffs (1986)
Otsu, N.: A threshold selection method from grey-level histograms. IEEE Trans. Systems Man Cybernet 9(1), 62–66 (1979)
Sauvola, J., Pietikainen, M.: Adaptive Document Image Binarization. Pattern Recognition 33, 225–236 (2000)
Shi, Z., Govindaraju, V.: Historical Document Image Segmentation Using Background Light Intensity Normalization. In: SPIE Document Recognition and Retrieval XII, San Jose, California, USA, January 16-20 (2005)
Yan, C., Leedham, G.: Decompose-Threshold Approach to Handwriting Extraction in Degraded Historical Document Images. In: Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR 2004), Kokubunji, Tokyo, Japan, October 2004, pp. 239–244 (2004)
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Kavallieratou, E., Antonopoulou, H. (2005). Cleaning and Enhancing Historical Document Images. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_86
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DOI: https://doi.org/10.1007/11558484_86
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29032-2
Online ISBN: 978-3-540-32046-3
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