Skip to main content
SpringerLink
Log in

Image/Video Compression with Artificial Neural Networks

  • Conference paper
Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living (IWANN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5518))

Included in the following conference series:

  • 1882 Accesses

Abstract

Both Information Compression and Parallel Processing are key issues nowadays. And both are our framework for our proposal. Our purpose was to accomplish an exhaustive study about patterns recognition using backpropagation neural networks with multilayer perceptron topology for its subsequent application to image and video compression. The mathematical study of learning algorithms and construction of neural nets encompassed the greater part of our time for this study. The next step was to design the most appropriate neural net for our objective through the paradigm of the oriented-object programming.

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 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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. Bentley, P.: Evolutionary Design by Computers. Morgan Kaufmann, San Francisco (1999)

    MATH  Google Scholar 

  2. Bond, A.H., Gasser, L.: Readings in Distributed artificial Intelligence. Morgan Kaufmann, San Francisco (1988)

    Google Scholar 

  3. Nagatnam, N., Koved, L., Nadalin, A.: Enterprise Java Security: Building Secure J2EE Applications. Addison-Wesley Professional, Reading (1999)

    Google Scholar 

  4. Zapico, D., Lebrero, D.: Compresión de imágenes con Redes Neuronales de Retro-propagación (Perceptrón Multicapa). In: Actas IX Congreso Nacional de Estudiantes de In-geniería de Sistemas, Santa Fé de Bogotá, Colombia (2000)

    Google Scholar 

  5. Rojas, R.: Neural Networks: A Systematic Introduction. Springer, Heidelberg (1996)

    Book  MATH  Google Scholar 

  6. Fuliang, Y., Jun, W., Chengan, G.: Advances in Neural Networks. Springer, Heidelberg (2004)

    Google Scholar 

  7. Chauvin, Y., Rumelhart, D.: Backpropagation: Theory, Architectures, and Applications. Lawrence Erlbaum Associates, Mahwah (1995)

    Google Scholar 

  8. Colin, F.: Hebbian Learning and Negative Feedback Networks. Springer, Heidelberg (2006)

    MATH  Google Scholar 

  9. Fausett, L.V.: Fundamentals of Neural Networks: Architectures, Algorithms, and Applications. Prentice-Hall, Englewood Cliffs (1994)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departamento de Lenguajes y sistemas informáticos, UPSAM, Madrid, Spain

    Daniel Zapico Palacio, Rubén González Crespo, Gloria García Fernández & Ignacio Rodríguez Novelle

Authors
  1. Daniel Zapico Palacio
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rubén González Crespo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gloria García Fernández
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ignacio Rodríguez Novelle
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Graduate School of Engineering, Osaka Prefecture University, Osaka, Japan

    Sigeru Omatu

  2. Department of Informatics / CCTC, University of Minho, Braga, Portugal

    Miguel P. Rocha

  3. MAmI Research Lab, University of Castilla-La Mancha,, Ciudad Real, Spain

    José Bravo

  4. Department of Informatics, University of Vigo, Ourense, Spain

    Florentino Fernández

  5. Grupo de Investigación GICAP, Área de Lenguajes Higher Polytechnic School, Universidad de Burgos, Burgos, Spain

    Emilio Corchado

  6. Higher Polytechnic School, University of Burgos, Burgos, Spain

    Andrés Bustillo

  7. Department of Informatics, University of Salamanca, Salamanca, Spain

    Juan M. Corchado

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Palacio, D.Z., Crespo, R.G., Fernández, G.G., Novelle, I.R. (2009). Image/Video Compression with Artificial Neural Networks. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_47

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02481-8_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02480-1

  • Online ISBN: 978-3-642-02481-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation