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International Workshop on Artificial Neural Networks

IWANN 1995: From Natural to Artificial Neural Computation pp 948–955Cite as

Texture classification on real time using semi-cover vector and an orthogonal neural network

  • Neural Networks for Perception
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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 930))

Abstract

A texture image classification system based on the semi-cover vector (SCV) and the bi-directional associative orthonormalized memory (BAOM) is described. The SCV is an statistic extraction method of texture features derived from the fractal geometry. It is invariant under geometric transformations. The BAOM is a neural network with a hidden layer of neurons that increases the learning capacity and reduces the noisy effect. This classifier works in real time and produces about 95.13% of correct classification rate.

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Author information

Authors and Affiliations

  1. Departamento de Tecnologia Informática y Computación, Universidad de Alicante, Apdo 99, Alicante, Spain

    D. Asensi Muñoz, A. Almagro León & F. Ibarra Picó

Authors
  1. D. Asensi Muñoz
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  2. A. Almagro León
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  3. F. Ibarra Picó
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Editor information

José Mira Francisco Sandoval

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© 1995 Springer-Verlag Berlin Heidelberg

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Asensi Muñoz, D., Almagro León, A., Ibarra Picó, F. (1995). Texture classification on real time using semi-cover vector and an orthogonal neural network. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_272

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  • DOI: https://doi.org/10.1007/3-540-59497-3_272

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59497-0

  • Online ISBN: 978-3-540-49288-7

  • eBook Packages: Springer Book Archive

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