Visual Saliency Detection in Natural Scene Images using a Selective Attention Model

Authors

  • Yesenia González UPIITA, Instituto Politécnico Nacional, México
  • Alan Solano UPIITA, Instituto Politécnico Nacional, México

Keywords:

Visual saliency detection, Selective attention, 2D Gabor filter, Data clustering, Competitive neural network

Abstract

This article presents visual saliency detection in natural scene images. Images are processed using RGB, HSI and CMY color models and use some combinations of color components to feed a selective attention model based on the application of a two-dimensional specialized Gabor filter, which gives some of the features (like edges and outstanding contrasts), to be later highlighted by a clustering stage and a competitive artificial neural network stage. The simulations results show that the system is able to perform visual saliency detection in simple scenes and show encouraging results in complex scenes. For the tests were used images in RGB color format of 640 × 480 pixels (VGA). The implementation was made in the MATLAB® language.

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Published

2017-11-01

How to Cite

[1]
Y. González and A. Solano, “Visual Saliency Detection in Natural Scene Images using a Selective Attention Model”, Memoria investig. ing. (Facultad Ing., Univ. Montev.), no. 15, pp. 59–70, Nov. 2017.

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Section

Articles