Three-Stage Method of Text Region Extraction from Diagram Raster Images

  • Jerzy SasEmail author
  • Andrzej Zolnierek
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 226)


In the paper the combined approach to the problem of text region recognition problem is presented. We focused our attention on the chosen case of text extraction problem from specific type of images where text is imposed over graphical layer of vector images (charts, diagrams, etc.). For such images we proposed three-stage method using OCR tools as some kind of feed-back in process of text region searching. Some experimental results and examples of practical applications of recognition method are also briefly described.


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  1. 1.
    Babu, G., Srimaiyee, P., Srikrishna, A.: Text extraction from hetrogenous images using mathematical morphology. Journal of Theoretical and Applied Information Technology, 39–47 (2010)Google Scholar
  2. 2.
    Epshtein, B., Ofek, E., Wexler, Y.: Detecting text in natural scenes with stroke width transform. In: Proc of IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 2963–2970 (2010)Google Scholar
  3. 3.
    Gllavata, J., Ewerth, R., Freisleben, B.: Proc. of 3rd International Symposium on Image and Signal Processing and Analysis, ISPA 2003, Rome, pp. 611–616 (2003)Google Scholar
  4. 4.
    Liu, X., Samarabandu, J.: Multiscale edge-based text extraction from complex images. In: Proc. of IEEE International Conference on Multimedia and Expo., pp. 1721–1724. IEEE Computer Society (2006)Google Scholar
  5. 5.
    Marti, U.V., Bunke, H.: Using a Statistical Language Model to Improve the Performance of an HMM-Based Cursive Handwritting Recognition System. Int. Journ. of Pattern Recognition and Artificial Intelligence 15, 65–90 (2001)CrossRefGoogle Scholar
  6. 6.
    Paleo, B.: Levenshtein distance: Two Application in Data Base Record Linkage and Natural Language processing. LAP Lambert Academic Publishing (2010)Google Scholar
  7. 7.
    Wang, K., Kangasb, J.: Character Location in Scene Images from Digital Camera. Pattern Recognition 36, 2287–2299 (2003)zbMATHCrossRefGoogle Scholar
  8. 8.
    Wu, V., Manamatha, R., Riseman, E.: Finding text in images. In: Proc. of the Second ACM International Conference on Digital Libraries, pp. 3–12 (1997)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Institute of Applied InformaticsWroclaw University of TechnologyWroclawPoland
  2. 2.Faculty of Electronics, Department of Systems and Computer NetworksWroclaw University of TechnologyWroclawPoland

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