Abstract
In this paper we propose to combine region-based and texture-based approaches for text detection in digital images. Our solution is based on a cascade filtering of image regions. First, we apply heuristic filtering to disregard certain non-textual areas. Second, we perform a more precise and expensive texture-based filtering using support vector machines and wavelet-based texture features. We have evaluated our approach with the ICDAR 2003 text locating competition benchmark collection and tools. The experimental results showed competitive performance of our solution by means of recall and precision compared to other text detection approaches participated in ICDAR 2003 and lower computational cost at the same time.
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
Chen, D.T., Odobez, J.M., Bourlard, H.: Text detection and recognition in images and video frames 37(3), 595–608 (2004)
Chen, X., Yuille, A.L.: Detecting and reading text in natural scenes. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. 336–373 (2004)
Epshtein, B., Ofek, E., Wexler, Y.: Detecting text in natural scenes with stroke width transform. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2963–2970 (June 2010)
Farhoodi, R., Kasaei, S.: Abstract text segmentation from images with textured ans colored background (2008)
Gllavata, J.: Extracting Textual Information from Images and Videos for Automatic Content-Based Annotation and Retrieval. Dissertation, Fachbereich Mathematik und Informatik der Philipps-Universitaet Marburg (2007)
Jiang, R., Qi, F., Xu, L., Wu, G.: Detecting and segmenting text from natural scenes with 2-stage classification. In: Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications, ISDA 2006, pp. 819–824. IEEE Computer Society, Washington, DC (2006)
Jolliffe, I.T.: Principal Component Analysis. Springer (1986), http://www.springer.com
Jung, K., Kim, K.I., Jain, A.K.: Text information extraction in images and video: a survey. Pattern Recognition 5, 977–997 (2004)
Lucas, S.M., Panaretos, A., Sosa, L., Wong, A.T.S., Ashida, K., Nagai, H., Okamoto, M., Yamamoto, H., Miyao, H., Zhu, J., Ou, W., Wolf, C., Jolion, J.M., Todoran, L., Worring, M., Lin, X.: X.: Icdar 2003 robust reading competitions: entries, results and future directions. International Journal on Document Analysis and Recognition - Special Issue on Camera-based Text and Document Recognition 7(2-3), 105–122 (2005)
Hiremath, P.S., Shivashankar, S.: Wavelet based features for texture classification. ICGST International Journal on Graphics, Vision and Image Processing 6, 55–58 (2006)
Tadeusiewicz, R.: How Intelligent Should Be System for Image Analysis? In: Kwasnicka, H., Jain, L.C. (eds.) Innovations in Intelligent Image Analysis. SCI, pp. VX. Springer, Heidelberg (2011), http://www.springer.com
Shim, J.-C., Dorai, C., Bolle, R.: Automatic text extraction from video for content-based annotation and retrieval. In: ICPR 1998: Proceedings of the 14th International Conference on Pattern Recognition, vol. 1, p. 618. IEEE Computer Society, Washington, DC (1998)
Tadeusiewicz, R.: What does it means ”automatic understanding of the images”? In: Proceedings of the 2007 IEEE International Workshop on Imaging Systems and Techniques, pp. 1–3 (May 2007)
Wolf, C., Jolion, J.-M.: Object count/area graphs for the evaluation of object detection and segmentation algorithms. International Journal on Document Analysis and Recognition 8(4), 280–296 (2006)
Wu, V., Manmatha, R.: andE.M. Riseman. Finding text in images. In: ACM International Conference on Digital libraries (DL), pp. 3–12 (1997)
Ye, Q.X., Huang, Q.M., Gao, W., Zhao, D.B.: Fast and robust text detection in images and video frames 23(6), 565–576 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Grzegorzek, M., Li, C., Raskatow, J., Paulus, D., Vassilieva, N. (2013). Texture-Based Text Detection in Digital Images with Wavelet Features and Support Vector Machines. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_84
Download citation
DOI: https://doi.org/10.1007/978-3-319-00969-8_84
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00968-1
Online ISBN: 978-3-319-00969-8
eBook Packages: EngineeringEngineering (R0)