Skip to main content
SpringerLink
Log in

Image Pattern Recognition

  • Reference work entry
Encyclopedia of Biometrics

Synonyms

Image classification; Image pattern classification; Image recognition

Definition

Image pattern recognition is the problem of exploring how to recognize image patterns. An image pattern recognition system generally consists of four parts: a camera that acquires the image samples to be classified, an image preprocessor that improves the qualities of images, a feature extraction mechanism that gains discriminative features from images for recognition, and a classification scheme that classifies the image samples based on the extracted features.

Introduction

Image is the most important pattern perceived everyday. A lot of biometric patterns, such as faces, fingerprints, palmprints, hands, iris, ears, are all shown in images. Image pattern recognition, therefore, the fundamental problem in pattern recognition area, particularly in biometrics. The process of an image pattern recognition task generally includes four steps: image acquisition, image preprocessing, image feature...

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 449.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Russ, J.C.: The Image Processing Handbook (4th edn.). Baker & Taylor Press, Charlotte, NC (2002)

    Google Scholar 

  2. Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–86 (1991)

    Article  Google Scholar 

  3. Belhumeur, P.N., Hespanha, J.P., Kriengman, D.J.: Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Machine Intell. 19(7), 711–720 (1997)

    Article  Google Scholar 

  4. Yang, J., Zhang, D., Frangi, A.F., Yang, J.-y.: Two-dimensional PCA: a new approach to face representation and recognition. IEEE Trans. Pattern Anal. Machine Intell. 26(1), 131–137 (2004)

    Article  Google Scholar 

  5. Yang, J., Liu, C.: Horizontal and vertical 2DPCA-based discriminant analysis for face verification on a large-scale database. IEEE Trans. Inf. Forensics Security. 2(4), 781–792 (2007)

    Article  Google Scholar 

  6. Yang, J., Yang, J.-y., Frangi, A.F., Zhang, D.: Uncorrelated projection discriminant analysis and its application to face image feature extraction. Intern. J. Pattern Recognit. Artif. Intell. 17(8), 1325–1347 (2003)

    Article  Google Scholar 

  7. Ye, J., Janardan, R., Li, Q.: Two-dimensional linear discriminant analysis. In: Proceedings of the Annual Conference on Advances in Neural Information Processing Systems (NIPS’04), Vancouver, BC, Canada (2004)

    Google Scholar 

  8. Daugman, J.G.: Uncertainty relations for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. J. Opt. Soc. Am. A. 2, 1160–1169 (1985)

    Article  Google Scholar 

  9. Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: application to face recognition. IEEE Trans. Pattern Anal. Machine Intell. 28(12), 2037–2041 (2006)

    Article  Google Scholar 

  10. Liu, C., Wechsler, H.: Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition. IEEE Trans. Image Process. 11(4), 467–476 (2002)

    Article  Google Scholar 

  11. Cover, T.M., Hart, P.E.: Nearest neighbor pattern classification. IEEE Trans. Inf. Theory. 13(1), 21–27 (1967)

    Article  MATH  Google Scholar 

  12. Fukunaga, K.: Introduction to Statistical Pattern Recognition (2nd edn.). Academic Press, New York (1990)

    Google Scholar 

  13. Li, S.Z., Lu, J.: Face recognition using the nearest feature line method. IEEE Trans. Neural Netw. 10(2), 439–443 (1999)

    Article  Google Scholar 

  14. Burge, C.J.C.: A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Disc. 2, 121–167 (1998)

    Article  Google Scholar 

  15. Jain, A.K., Duin, R.P.W., Mao, J.: Statistical pattern recognition: a review. IEEE Trans. Pattern Anal. Machine Intell. 22(1), 4–37 (2000)

    Article  Google Scholar 

  16. Generalization error. http://en.wikipedia.org/wiki/Generalization_error

Download references

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China

    Jian Yang & Jingyu Yang

Authors
  1. Jian Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jingyu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Center for Biometrics and Security Research, Chinese Academy of Sciences, Beijing, China

    Stan Z. Li (Professor) (Professor)

  2. Departments of Computer Science & Engineering, Michigan State University, East Lansing, MI, USA

    Anil Jain (Professor) (Professor)

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this entry

Cite this entry

Yang, J., Yang, J. (2009). Image Pattern Recognition. In: Li, S.Z., Jain, A. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73003-5_223

Download citation

Publish with us

Policies and ethics

Search

Navigation