Visual Saliency Detection Using a Rule-Based Aggregation Approach
AbstractIn this paper, we propose an approach for salient pixel detection using a rule-based system. In our proposal, rules are automatically learned by combining four saliency models. The learned rules are utilized for the detection of pixels of the salient object in a visual scene. The proposed methodology consists of two main stages. Firstly, in the training stage, the knowledge extracted from outputs of four state-of-the-art saliency models is used to induce an ensemble of rough-set-based rules. Secondly, the induced rules are utilized by our system to determine, in a binary manner, the pixels corresponding to the salient object within a scene. Being independent of any threshold value, such a method eliminates any midway uncertainty and exempts us from performing a post-processing step as is required in most approaches to saliency detection. The experimental results on three datasets show that our method obtains stable and better results than state-of-the-art models. Moreover, it can be used as a pre-processing stage in computer vision-based applications in diverse areas such as robotics, image segmentation, marketing, and image compression. View Full-Text
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Lopez-Alanis, A.; Lizarraga-Morales, R.A.; Sanchez-Yanez, R.E.; Martinez-Rodriguez, D.E.; Contreras-Cruz, M.A. Visual Saliency Detection Using a Rule-Based Aggregation Approach. Appl. Sci. 2019, 9, 2015.
Lopez-Alanis A, Lizarraga-Morales RA, Sanchez-Yanez RE, Martinez-Rodriguez DE, Contreras-Cruz MA. Visual Saliency Detection Using a Rule-Based Aggregation Approach. Applied Sciences. 2019; 9(10):2015.Chicago/Turabian Style
Lopez-Alanis, Alberto; Lizarraga-Morales, Rocio A.; Sanchez-Yanez, Raul E.; Martinez-Rodriguez, Diana E.; Contreras-Cruz, Marco A. 2019. "Visual Saliency Detection Using a Rule-Based Aggregation Approach." Appl. Sci. 9, no. 10: 2015.
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