Skip to main content
SpringerLink
Log in

Features Invariant Simultaneously to Convolution and Affine Transformation

  • Conference paper
  • First Online:
Computer Analysis of Images and Patterns (CAIP 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2124))

Included in the following conference series:

Abstract

The contribution is devoted to the recognition of objects and patterns deformed by imaging geometry as well as by unknown blurring. We introduce a new class of features invariant simultaneously to blurring with a centrosymmetric PSF and to affine transformation. As we prove in the contribution, they can be constructed by combining affine moment invariants and blur invariants derived earlier. Combined invariants allow to recognize objects in the degraded scene without any restoration.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Mundy, J.L., Zisserman, A.: Geometric Invariance in Computer Vision. MIT Press (1992)

    Google Scholar 

  2. Reiss, T.H.: Recognizing Planar Objects using Invariant Image Features. Lecture Notes in Computer Science, Vol. 676. Springer, Berlin (1993)

    MATH  Google Scholar 

  3. Hu, M.K.: Visual pattern recognition by moment invariants. IRE Trans. Information Theory, 8 (1962) 179–187

    Google Scholar 

  4. Belkasim, S.O., Shridhar, M., Ahmadi, M.: Pattern recognition with moment invariants: a comparative study and new results. Pattern Recognition, 24 (1991) 1117–1138

    Article  Google Scholar 

  5. Arbter, K., Snyder, W.E., Burkhardt, H., Hirzinger, G.: Application of affine-invariant Fourier descriptors to recognition of 3-D objects. IEEE Trans. Pattern Analysis and Machine Intelligence, 12 (1990) 640–647

    Article  Google Scholar 

  6. Weiss, I.: Projective invariants of shapes. In: Proc. Image Understanding Workshop. Cambridge, Mass. (1988) 1125–1134

    Google Scholar 

  7. Suk, T., Flusser, J.: Vertex-based features for recognition of projectively deformed polygons. Pattern Recognition, 29 (1996) 361–367

    Article  Google Scholar 

  8. Lenz, R., Meer, P.: Point configuration invariants under simultaneous projective and permutation transformations. Pattern Recognition, 27 (1994) 1523–1532

    Article  Google Scholar 

  9. van Gool, L., Moons, T., Ungureanu, D.: Affine/photometric invariants for planar intensity patterns. In: Proc. 4th ECCV’96, LNCS Vol. 1064. Springer (1996) 642–651

    Google Scholar 

  10. Mindru, F., Moons, T., van Gool, L.: Recognizing color patterns irrespective of viewpoint and illumination. In: Proc. IEEE Conf. Computer Vision Pattern Recognition CVPR’99, Vol. 1 (1999) 368–373

    Google Scholar 

  11. Schmid, C., Mohr, R.: Local grayvalue invariants for image retrieval. IEEE Trans. Pattern Analysis and Machine Intelligence, 19 (1997) 530–535

    Article  Google Scholar 

  12. Flusser, J., Suk, T.: Degraded image analysis: An invariant approach. IEEE Trans. Pattern Analysis and Machine Intelligence, 20 (1998) 590–603

    Article  Google Scholar 

  13. Flusser, J., Suk, T., Saic, S.: Recognition of blurred images by the method of moments. IEEE Transactions on Image Processing, 5 (1996) 533–538

    Article  Google Scholar 

  14. Zhang, Y., Wen, C., Zhang, Y.: Estimation of motion parameters from blurred images. Pattern Recognition Letters, 21 (2000) 425–433

    Article  MathSciNet  Google Scholar 

  15. Lu, J., Yoshida, Y.: Blurred image recognition based on phase invariants. IEICE Trans. Fundamentals of El. Comm. and Comp. Sci., E82A (1999) 1450–1455

    Google Scholar 

  16. Zhang, Y., Zhang, Y., Wen, C.: A new focus measure method using moments. Image and Vision Computing, 18 (2000) 959–965

    Article  Google Scholar 

  17. Flusser, J., Suk, T., Saic, S.: Image features invariant with respect to blur. Pattern Recognition, 28 (1995) 1723–1732

    Article  Google Scholar 

  18. Flusser, J., Suk, T., Saic, S.: Recognition of images degraded by linear motion blur without restoration. Computing Suppl., 11 (1996) 37–51

    MathSciNet  Google Scholar 

  19. Flusser, J., Zitová, B.: Combined invariants to linear filtering and rotation. Intl. J. Pattern Recognition Art. Intell., 13 (1999) 1123–1136

    Article  Google Scholar 

  20. Flusser, J., Zitová, B., Suk, T.: Invariant-based registration of rotated and blurred images. In: Tammy, I.S. (ed.): IEEE 1999 International Geoscience and Remote Sensing Symposium. Proceedings. IEEE Computer Society, Los Alamitos (June 1999) 1262–1264

    Google Scholar 

  21. Reiss, T.H.: The revised fundamental theorem of moment invariants. IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13 (1991) 830–834

    Article  Google Scholar 

  22. Flusser, J., Suk, T.: Pattern recognition by affine moment invariants. Pattern Recognition, 26 (1993) 167–174

    Article  MathSciNet  Google Scholar 

  23. Schur, I.: Vorlesungen über Invariantentheorie. Springer, Berlin (1968)

    MATH  Google Scholar 

  24. Gurevich, G.B.: Foundations of the Theory of Algebraic Invariants. Nordhoff, Groningen, The Netherlands (1964)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Pod vodárenskou věží 4, 182 08, Praha 8, Czech Republic

    Tomáš Suk & Jan Flusser

Authors
  1. Tomáš Suk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jan Flusser
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculty of Electronics and Information Technology Institute of Radioelectronics, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665, Warsaw, Poland

    Władysław Skarbek

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Suk, T., Flusser, J. (2001). Features Invariant Simultaneously to Convolution and Affine Transformation. In: Skarbek, W. (eds) Computer Analysis of Images and Patterns. CAIP 2001. Lecture Notes in Computer Science, vol 2124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44692-3_23

Download citation

  • DOI: https://doi.org/10.1007/3-540-44692-3_23

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42513-7

  • Online ISBN: 978-3-540-44692-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation