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IAPR Workshop on Artificial Neural Networks in Pattern Recognition

ANNPR 2012: Artificial Neural Networks in Pattern Recognition pp 213–224Cite as

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Grayscale Images and RGB Video: Compression by Morphological Neural Network

Grayscale Images and RGB Video: Compression by Morphological Neural Network

  • Osvaldo de Souza22,
  • Paulo César Cortez22 &
  • Francisco A. T. F. da Silva23 
  • Conference paper
  • 1347 Accesses

Part of the Lecture Notes in Computer Science book series (LNAI,volume 7477)

Abstract

This paper investigates image and RGB video compression by a supervised morphological neural network. This network was originally designed to compress grayscale image and was then extended to RGB video. It supports two kinds of thresholds: a pixel-component threshold and pixel-error counting threshold. The activation function is based on an adaptive morphological neuron, which produces suitable compression rates even when working with three color channels simultaneously. Both intra-frame and inter-frame compression approaches are implemented. The PSNR level indicates that the compressed video is compliant with the desired quality levels. Our results are compared to those obtained with commonly used image and video compression methods. Network application results are presented for grayscale images and RGB video with a 352 × 288 pixel size.

Keywords

  • Supervised Morphological Neural Network
  • RGB Video Compression
  • Image Compression

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Author information

Authors and Affiliations

  1. DETI, Federal University of Ceará, Fortaleza, Brazil

    Osvaldo de Souza & Paulo César Cortez

  2. National Institute For Space Research, ROEN, Eusébio, Brazil

    Francisco A. T. F. da Silva

Authors
  1. Osvaldo de Souza
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  2. Paulo César Cortez
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  3. Francisco A. T. F. da Silva
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Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler (FBK), 38123, Trento, Italy

    Nadia Mana

  2. Institute of Neural Information Processing, University of Ulm, 89069, Ulm, Germany

    Friedhelm Schwenker

  3. Dipartimento di Ingegneria dell’Informazione, Università di Siena, 53100, Siena, Italy

    Edmondo Trentin

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

de Souza, O., Cortez, P.C., da Silva, F.A.T.F. (2012). Grayscale Images and RGB Video: Compression by Morphological Neural Network. In: Mana, N., Schwenker, F., Trentin, E. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2012. Lecture Notes in Computer Science(), vol 7477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33212-8_20

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  • DOI: https://doi.org/10.1007/978-3-642-33212-8_20

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  • Print ISBN: 978-3-642-33211-1

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