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A CNN model for grey scale image processing

  • Miguel A. Jaramillo-Morán
  • Francisco J. López-Aligué
  • Miguel Macías-Macías
  • María I. Acevedo-Sotoca
Neural Networks for Perception
Part of the Lecture Notes in Computer Science book series (LNCS, volume 930)

Abstract

A modification of the CNN model is proposed in this work. An iterated-map is defined instead of the original differential equation while a sigmoid function is taken as the cell output. Modifications in the structure and values of the synaptic scheme allow the use of the model in different tasks. The network's behaviour is mainly determined by its feedforward term, while feedback simply adds optimization to the network's output The network's stability is discussed. Edge detection and contrast enhancement are performed, stressing the fact that they are only different aspects of the same network property: the enhancement of brightness gradients. Some examples are presented in which grey scale images are processed, revealing the capabilities of the model both in detecting edges and in enhancing contrasts.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Miguel A. Jaramillo-Morán
    • 1
  • Francisco J. López-Aligué
    • 1
  • Miguel Macías-Macías
    • 1
  • María I. Acevedo-Sotoca
    • 1
  1. 1.Departamento de Electrónica e Ingeniería Electromecánica. Facultad de CienciasUniversidad de ExtremaduraBadajozSpain

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