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

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, w...

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Hovedforfatter: González, Yesenia (author)
Andre forfattere: Solano, Alan (author)
Format: article
Sprog:spansk
Udgivet: 2017
Fag:
Obtención de rasgos preponderantes
Atención selectiva
Filtro de Gabor en 2D
Agrupamiento de datos
Red neuronal de competencia
Visual saliency detection
Selective attention
2D Gabor filter
Data clustering
Competitive neural network
Online adgang:http://revistas.um.edu.uy/index.php/ingenieria/article/view/306
https://hdl.handle.net/20.500.12806/2481
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Summary: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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