Abstract
In this paper we propose a new texture-based method for extraction of text areas in a complex document image. Gabor filter, motivated by the multi-channel filtering approach of Human Visual System (HVS), has been employed to create energy map of the document. In this energy map we assumed that text areas were rich in high frequency components. Connected components (probable text characters) were extracted by binarization of the energy map with Otsu’s adaptive threshold method. First non-text components such as pictures, lines, frames etc. were eliminated by Gabor filtering. As a novel approach, remaining non-text components were then eliminated by using character component interval tracing. Elimination that formed in two stage, enhanced the success of detecting text area on different kinds of digital documents.
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.
Similar content being viewed by others
References
Simon, A., Pret, J.-C., Peter Johnson, A.: A Fast Algorithm for Bottom-Up Document Layout Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(3), 273–277 (1997)
Ha, J., Haralick, R., Phillips, I.: Document Page Decomposition by the Bounding-Box Projection Technique. In: Proc. Third Int’l Conf. Document Analysis and Recognition, pp. 1,119–1,122, Montreal (1995)
Jain, A.K., Yu, B.: Document representation and its application to page decomposition. IEEE Trans. Pattern Analysis and Machine Intelligence 20, 294–308 (1998)
Chen, J.-L.: A simplified approach to the HMM based texture analysis and its application to document segmentation. Pattern Recognition Letters 18(10), 993–1007 (1997)
Yuan, Q., Tan, C.L.: Page segmentation and text extraction from gray-scale images in microfilm. SPIE Document Recognition and Retrieval VIII, pp. 323-332 (2001)
Raju, S.S., Pati, P.B., Ramakrishnan, A.G.: Gabor Filter Based Block Energy Analysis for Text Extraction from Digital Document Images. In: DIAL 2004. Proceedings First International Workshop on Document Image Analysis for Libraries, pp. 233–243 (2004)
Pati, P.B., Raju, S., Pati, N., Ramakrishnan, A.G.: Gabor filters for document analysis in Indian Bilingual Documents. In: Proc. of International Conference on Intelligent Sensing and Information Processing - 2004, Chennai, India, pp. 123–126 (2004)
Gonzales, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice-Hall, Englewood Cliffs, NJ (2002)
Young, I., van Vliet, L., van Ginkel, M.: Recursive Gabor filtering. IEEE Trans. Sig. Proc. 50(11), 2799–2805 (2002)
Lee, T.S.: Image representation using 2D Gabor wavelets. IEEE Trans.Pattern Anal. Machine Intell. 18, 959–971 (1996)
Otsu, N.: A Threshold Selection Method From Gray Level Histograms. IEEE trans. Syst. Man. Cybercet., SMC, 62–66 (1979)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ar, I., Karsligil, M.E. (2007). Text Area Detection in Digital Documents Images Using Textural Features. In: Kropatsch, W.G., Kampel, M., Hanbury, A. (eds) Computer Analysis of Images and Patterns. CAIP 2007. Lecture Notes in Computer Science, vol 4673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74272-2_69
Download citation
DOI: https://doi.org/10.1007/978-3-540-74272-2_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74271-5
Online ISBN: 978-3-540-74272-2
eBook Packages: Computer ScienceComputer Science (R0)