Texture Classification with Neural Networks

  • William Raveane
  • María Angélica González Arrieta
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 217)

Abstract

Texture classification poses a well known difficulty within computer vision systems. This paper reviews a method for image segmentation based on the classification of textures using artificial neural networks. The supervised machine learning system developed here is able to recognize and distinguish among multiple feature regions within one or more photographs, where areas of interest are characterized by the various patterns of color and shape they exhibit. The use of an enhancement filter to reduce sensitivity to illumination and orientation changes in images is explored, as well as various post-processing techniques to improve the classification results based on context grouping. Various applications of the system are examined, including the geographical segmentation of satellite images and a brief overview of the model’s performance when employed on a real time video stream.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • William Raveane
    • 1
  • María Angélica González Arrieta
    • 1
  1. 1.Universidad de SalamancaSalamancaEspaña

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