Skip to main content

Feature Extraction

  • Chapter
Book cover Applied Image Processing

Part of the book series: Macmillan New Electronics Series

  • 87 Accesses

Abstract

The feature extraction aspect of image analysis seeks to identify inherent characteristics, or features, of objects found within an image. These characteristics are used to describe the object, or attributes of the object, prior to the subsequent task of classification. Feature extraction operates on two-dimensional image arrays but produces a list of descriptions, or a ‘feature vector’ (note the change in information format indicated on the generic model, section 1.4.1).

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J. Serra, Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.

    Google Scholar 

  2. G. Matheron, Random Sets and Integral Geometry, Wiley, New York, 1975.

    Google Scholar 

  3. A. Netravali and J. Limb, ‘Picture coding: a review’, Proc. IEEE68, No. 3, pp. 366–406, 1980.

    Article  Google Scholar 

  4. A. Jain, P. Farrelle and V. Algazi, ‘Image data compression’, in M. Ekstrom (Ed.), Digital Image Processing Techniques, Academic Press, New York, 1984.

    Google Scholar 

  5. Various authors, Proc. IEEE 73, No. 2, 1985.

    Google Scholar 

  6. H. Freeman, ‘Computer processing of line-drawing images’, ACM Computing Surveys, 6(1), pp. 57–97, 1974.

    Article  Google Scholar 

  7. R. Courant and H. Robbins, What is Mathematics?, pp. 267–269, Oxford University Press, London, 1941.

    Google Scholar 

  8. K. Dunkelburger and O. Mitchell, ‘Contour tracing for precision measurement’, Proc. Int. Conf. Robotics & Automation, pp. 22–27, IEEE, 1985.

    Google Scholar 

  9. J. Dessimoz and P. Kammenos, ‘Software or hardware for robot vision’, in I. Aleksander (Ed.), Artificial Vision for Robots, Chapter 2, Kogan Page, London, 1983.

    Google Scholar 

  10. H. Blum, ‘A transformation for extracting new descriptors of shape’, in W. Wathen-Dunn (Ed.), Symp. Models for the Perception of Speech and the Visual Form, MIT Press, Cambridge, Massachusetts, 1967.

    Google Scholar 

  11. P. Kitchin and A. Pugh, ‘Processing of binary images’, in A. Pugh (Ed.), Robot Vision, pp. 21–42, IFS (Publications), Bedford, 1983.

    Chapter  Google Scholar 

  12. R. Gonzalez and R. Woods, Digital Image Processing, 2nd edn, Addison-Wesley, London, 1992.

    Google Scholar 

  13. R. Haralick, Statistical and structural approaches to texture’, Proc. IEEE67, pp. 786–809, 1979.

    Article  Google Scholar 

  14. R. Haralick, Image Texture Analysis, Plenum Press, New York, 1981.

    Google Scholar 

  15. B. Lipkin and A. Rosenfeld (Eds), Picture Processing and Psycho-pictorics, Academic Press, New York, 1970.

    Google Scholar 

  16. M. Hu, ‘Visual pattern recognition by moment invariants’, IRE Trans. Info. Theory, IT-8, pp. 179–187, 1962.

    Google Scholar 

  17. S. Dudani, K. Breeding and R. McGhee, ‘Aircraft identification by moment invariants’, IEEE Trans. Computers, 26(1) pp. 39–46, 1977.

    Article  Google Scholar 

  18. R. Wong and E. Hall, ‘Scene matching with moment invariants’, CGIP, 8, pp. 16–24, 1978.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Copyright information

© 1995 G.J. Awcock and R. Thomas

About this chapter

Cite this chapter

Awcock, G.J., Thomas, R. (1995). Feature Extraction. In: Applied Image Processing. Macmillan New Electronics Series. Palgrave, London. https://doi.org/10.1007/978-1-349-13049-8_6

Download citation

  • DOI: https://doi.org/10.1007/978-1-349-13049-8_6

  • Publisher Name: Palgrave, London

  • Print ISBN: 978-0-333-58242-8

  • Online ISBN: 978-1-349-13049-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics