Principal Component Analysis of Point Distance Histogram for Recognition of Stamp Silhouettes

  • Paweł Forczmański
  • Dariusz Frejlichowski
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 102)


The paper presents a problem of stamp shape recognition. A stamp is given as a bitmap containing binary values, and may be represented by a specific geometrical form coming from the tradition of stamping process, which includes round, oval, square, rectangular or triangular shapes. While the problem of stamp detection, localization and extraction was addressed in several previous publications, in this paper we deal with the stage of features extraction and reduction, by means of Point Distance Histogram (at the stage of features extraction) and Principal Component Analysis (at the stage of dimensionality reduction). The final classification employs similarity evaluation involving hand-drawn templates, ideal shapes and average descriptors calculated for the entire database. The paper provides also some experimental results on real documents with different types of stamps and a comparison with a classical PCA applied on image matrix.


Principal Component Analysis Dimensionality Reduction Discrete Cosine Transform Recognition Rate Average Descriptor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ueda, K., Nakamura, Y.: Automatic verification of seal impression patterns. In: Proc. 7th. Int. Conf. on Pattern Recognition, pp. 1019–1021 (1984)Google Scholar
  2. 2.
    Pham, T.D.: Unconstrained logo detection in document images. Pattern Recognition 36, 3023–3025 (2003)zbMATHCrossRefGoogle Scholar
  3. 3.
    Zhu, G., Jaeger, S., Doermann, D.: A robust stamp detection framework on degraded documents. In: Proceedings — SPIE The International Society For Optical Engineering, vol. 6067 (2006)Google Scholar
  4. 4.
    Zhu, G., Doermann, D.: Automatic Document Logo Detection. In: The 9th International Conference on Document Analysis and Recognition ICDAR, pp. 864–868 (2007)Google Scholar
  5. 5.
    He, J., Downton, A.C.: Configurable Text Stamp Identification Tool with Application of Fuzzy Logic. In: Marinai, S., Dengel, A.R. (eds.) DAS 2004. LNCS, vol. 3163, pp. 134–151. Springer, Heidelberg (2004)Google Scholar
  6. 6.
    Frejlichowski, D., Forczmański, P.: General Shape Analysis Applied to Stamps Retrieval from Scanned Documents. In: Dicheva, D., Dochev, D. (eds.) AIMSA 2010. LNCS, vol. 6304, pp. 251–260. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Forczmański, P., Frejlichowski, D.: Robust Stamps Detection and Classification by Means of General Shape Analysis. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) ICCVG 2010. LNCS, vol. 6374, pp. 360–367. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  8. 8.
    Frejlichowski, D.: The Point Distance Histogram for Analysis of Erythrocyte Shapes. Polish Journal of Environmental Studies 16(5b), 261–264 (2007)Google Scholar
  9. 9.
    Forczmański, P., Frejlichowski, D.: Efficient stamps classification by means of point distance histogram and discrete cosine transform. In: Burduk, R., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds.) Computer Recognition Systems 4. AISC, vol. 95, pp. 327–336. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  10. 10.
    Jolliffe, I.T.: Principal Component Analysis. Springer, NY (1986)Google Scholar
  11. 11.
    Kukharev, G., Forczmański, P.: Data Dimensionality Reduction for Face Recognition. Machine Graphics & Vision 13(1/2), 99–122 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Paweł Forczmański
    • 1
  • Dariusz Frejlichowski
    • 1
  1. 1.Faculty of Computer Science and Information TechnologyWest Pomeranian University of TechnologySzczecinPoland

Personalised recommendations