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Advances in Intelligent Image Analysis

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 339))

Abstract

This chapter presents some recent advances in the area of computer vision. The various stages involved in the area of image processing and their interpretation are described. The first step is that of image registration. That is, the overlay two or more images of the same scene. These are taken from different viewpoints, at different times or possibly by different sensors. The next phase is image preprocessing. This mainly involves image enhancement and clearing for example. Other problem is that of image analysis. This is the extraction of important features of the image. Having obtained a description of the image, the process of object (pattern) recognition can be performed. All of these tasks are very important and useful, they still do not give a semantic interpretation of images. Image interpretation, similar image searching is still a major challenge facing researchers. The second part of this chapter summarises the remaining chapters of the book.

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References

  1. Bieniecki, W., Grabowski, S., Rozenberg, W.: Image Preprocessing for Improving OCR Accuracy. In: International Conference on Perspective Technologies and Methods in MEMS Design, MEMSTECH 2007 (2007)

    Google Scholar 

  2. Davies, E.R.: Machine Vision: Theory, Algorithms, Practicalities. Morgan Kaufmann, San Francisco (2004)

    Google Scholar 

  3. Dickinson, S.J., Leonardis, A., Schiele, B., Tarr, M.J. (eds.): Object Categorization: Computer and Human Vision Perspectives. Cambridge University Press, Cambridge (2009)

    Google Scholar 

  4. O’Gorman, L., Sammon, M.J., Seul, M.: Cambridge University Press, Cambridge (2008)

    Google Scholar 

  5. Häder, D.P.: Image analysis: methods and applications. CRC Press, Boca Raton (2001)

    Google Scholar 

  6. van der Heide, A., Urano, T., Polderdijk, F., de Haan, W., Bosiers, J.T.: IDEAL: An image pre-processing architecture for high-end professional DSC applications. In: SPIE Electronic Imaging 2009, pp. 7250–7238 (2009)

    Google Scholar 

  7. Heusch, G., Rodriguez, Y., Marcel, S.: Local Binary Patterns as an Image Preprocessing for Face Authentication. In: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition (FGR 2006) (2006)

    Google Scholar 

  8. Huang, T.S., Aizawa, K.: Image Processing: Some Challenging Problems. PNAS 90, 9766–9769 (1993)

    Article  Google Scholar 

  9. Inoue M.: On the need for annotation-based image retrieval. In: Proceedings of the Information Retrieval in Context (IRiX), A Workshop at SIGIR 2004, pp. 44–46 (2004)

    Google Scholar 

  10. Lavrenko, V., Manmatha, R., Jeon, J.: A model for learning the semantics of pictures. In: Proceedings of Neural Information Processing Systems (NIPS). MIT Press, Cambridge (2003)

    Google Scholar 

  11. Luger, G.F., Stubblefield, W.A.: Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 2nd edn. Benjamin Cummings, Palo Alto (1993)

    Google Scholar 

  12. Maier, O., Stanek, M., Kwaśnicka, H.: PATSI - photo annotation through similar images with annotation length optimization. In: Kłopotek, M.A. et al. (eds.) Intelligent information systems, pp. 219–232. Publishing House of University of Podlasie (2010)

    Google Scholar 

  13. Mian, A.S., Bennamoun, M., Owens, R.A.: An efficient multimodal 2D-3D hybrid approach to automatic face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(11), 1927–1943 (2007)

    Article  Google Scholar 

  14. Robert, J., Schalkoff, R.J.: Artificial Intelligence: An Engineering Approach. McGraw-Hill College, New York (1990)

    Google Scholar 

  15. Stanek, M., Broda, B., Kwasnicka, H.: PATSI — photo annotation through finding similar images with multivariate gaussian models. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) ICCVG 2010. LNCS, vol. 6375, pp. 284–291. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. Tadeusiewicz, R., Ogiela, M.: Medical Image Understanding Technology. Springer-Verlag GmbH (2004)

    Google Scholar 

  17. Zitova, B., Flusser, J.: Image registration methods: a survey. Image and Vision Computing 21, 977–1000 (2003)

    Article  Google Scholar 

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Kwaśnicka, H., Jain, L.C. (2011). Advances in Intelligent Image Analysis. In: Kwaśnicka, H., Jain, L.C. (eds) Innovations in Intelligent Image Analysis. Studies in Computational Intelligence, vol 339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17934-1_1

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  • DOI: https://doi.org/10.1007/978-3-642-17934-1_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17933-4

  • Online ISBN: 978-3-642-17934-1

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