Abstract
Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cao, R., Tan, C.: Text/graphics separation in maps. In: Blostein, D., Kwon, Y.-B. (eds.) GREC 2001. LNCS, vol. 2390, p. 167. Springer, Heidelberg (2002)
Fletcher, L.A., Kasturi, R.: A robust algorithm for text string separation from mixed text/graphics images. IEEE Transactions on PAMI 10(6), 910–918 (1988)
Tombre, K., Tabbone, S., Peissier, L., Lamiroy, B., Dosch, P.: Text/Graphics separation revisited. In: Lopresti, D.P., Hu, J., Kashi, R.S. (eds.) DAS 2002. LNCS, vol. 2423, pp. 200–211. Springer, Heidelberg (2002)
Luo, H., Agam, G., Dinstein, I.: Directional mathematical morphology approach for line thinning and extraction of character strings from maps and line drawings. In: Proceedings of the ICDAR, Washington, DC, USA, p. 257 (1995)
Tan, C.L., Ng, P.O.: Text extraction using pyramid. Pattern Recognition 31(1), 63–72 (1998)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91–110 (2004)
Bicego, M., Lagorio, A., Grosso, E., Tistarelli, M.: On the use of SIFT features for face authentication. In: Proceedings of CVPRW, USA, p. 35 (2006)
Rusiñol, M., Lladós, J.: Word and Symbol Spotting Using Spatial Organization of Local Descriptors. In: Proceedings of IAPR Workshop on DAS, pp. 489–496 (2008)
Ballard, D.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13(2), 111–122 (1981)
Tombre, K., Lamiroy, B.: Graphics recognition - from re-engineering to retrieval. In: Proceedings of the ICDAR, pp. 148–155 (2003)
Roy, P.P., Pal, U., Lladós, J., Delalandre, M.: Multi-oriented and multi-sized touching character segmentation using dynamic programming. In: Proceedings of ICDAR, Barcelona, Spain, pp. 11–15 (2009)
Vapnik, V.: The Nature of Statistical Learning Theory. Springer, Heidelberg (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Roy, P.P., Pal, U., Lladós, J. (2010). Touching Text Character Localization in Graphical Documents Using SIFT. In: Ogier, JM., Liu, W., Lladós, J. (eds) Graphics Recognition. Achievements, Challenges, and Evolution. GREC 2009. Lecture Notes in Computer Science, vol 6020. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13728-0_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-13728-0_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13727-3
Online ISBN: 978-3-642-13728-0
eBook Packages: Computer ScienceComputer Science (R0)