Abstract
This paper proposes a new method for content-based image retrieval that uses a computational model of visual attention and genetic algorithm to find a given object in a set of images with different backgrounds. This method is composed by three main modules: a visual attention model that is quite robust against affine transformations; a color-based schematic representation of visual information; and a genetic algorithm that optimizes several parameters of the visual attention model in order to focus the attention mechanism on those regions of the image where it is most likely that a given object is present. The proposed method is validated through several experiments, and these experiments show that it can find the images that contain the sought object as well as the position and scale of the object in these images.
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Heinen, M.R., Engel, P.M. (2012). Image Retrieval by Content Based on a Visual Attention Model and Genetic Algorithms. In: Barros, L.N., Finger, M., Pozo, A.T., Gimenénez-Lugo, G.A., Castilho, M. (eds) Advances in Artificial Intelligence - SBIA 2012. SBIA 2012. Lecture Notes in Computer Science(), vol 7589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34459-6_13
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DOI: https://doi.org/10.1007/978-3-642-34459-6_13
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