Abstract
Skeletonisation is a key process in character recognition in natural images. Under the assumption that a character is made of a stroke of uniform colour, with small variation in thickness, the process of recognising characters can be decomposed in the three steps. First the image is segmented, then each segment is transformed into a set of connected strokes (skeletonisation), which are then abstracted in a descriptor that can be used to recognise the character. The main issue with skeletonisation is the sensitivity with noise, and especially, the presence of holes in the masks. In this article, a new method for the extraction of strokes is presented, which address the problem of holes in the mask and does not use any parameters.
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References
Epshtein, B., Ofek, E., Wexler, Y.: Detecting text in natural scenes with stroke width transform. In: Conference on Vision and Pattern Recognition, pp. 2963–2970 (2010)
Karatzas, D., Antonacopoulos, A.: Colour text segmentation in web images based on human perception. Image and Vision Computing 25(5), 564–577 (2007)
Cheriet, M., Kharma, N., Liu, C.L., Suen, C.Y.: Character Recognition Systems. Wiley Publishing Inc. (2007)
Parker, J.: Algorithms for Image Processing and Computer Vision. Wiley Publishing Inc. (2010)
Fan, K.C., Chen, D.F., Wen, M.G.: Skeletonization of binary images with nonuniform width via block decomposition and contour vector matching. Pattern Recognition 31, 823–838 (1998)
LeBourgeois, F., Emptoz, H.: Skeletonization by gradient regularization and diffusion. In: International Conference on Document Analysis and Recognition, vol. 2, pp. 1118–1122 (2007)
Yu, Z., Bajaj, C.: A segmentation-free approach for skeletonization of gray-scale images via anisotropic vector diffusion. In: Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1 (2004)
Ashok, M., SreeDevi, J., Bai, M.R.: An approach to noisy image skeletonization using morphological methods. International Journal of Scientific and Engineering Research 3 (2012)
Braquelaire, J.P., Vialard, A.: Euclidean paths: A new representation of boundary of discrete regions. Graphical Models and Image Processing 61, 16–43 (1999)
Bron, C., Kerbosch, J.: Algorithm 457: finding all cliques of an undirected graph. Communications of the ACM 16, 575–577 (1973)
Lucas, S.M., Panaretos, A., Sosa, L., Tang, A., Wong, S., Young, R.: Icdar 2003 robust reading competitions. In: Proceedings of the Seventh International Conference on Document Analysis and Recognition, ICDAR 2003, p. 682. IEEE Computer Society, Washington, DC (2003)
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Berger, C. (2014). Strokes Detection for Skeletonisation of Characters Shapes. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_49
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DOI: https://doi.org/10.1007/978-3-319-14364-4_49
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14363-7
Online ISBN: 978-3-319-14364-4
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