Region Based Image Preprocessor for Feed-Forward Perceptron Based Systems

  • Keith A. GreenhowEmail author
  • Colin G. Johnson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8866)


In this paper, we investigate the notion that there may be alternate methods, beyond typical rectilinear interpolations such as Bilinear Interpolation, that have a greater suitability for use in visual/image preprocessors for Artificial Neural Networks. We present a novel method for down-sampling image data in preparation for a Feed-Forward Perceptron system assisted by a neural usefulness metric, inspired by those common to pruning algorithms. This new method achieves greater accuracy compared to the same system using by Bilinear Interpolation, and has a reduced computational time.


Artificial neural networks Preprocessor Image processing Salience Relevance assessment 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.School of ComputingUniversity of KentCanterbury, KentUK

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