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Sensors 2019, 19(2), 421;

Appearance-Based Salient Regions Detection Using Side-Specific Dictionaries

School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
School of Management, Xi’an Jiaotong University, Xi’an 710049, China
School of Science, MOE Key Laboratory for Non-equilibrium Synthesis and Modulation of Condensed Matter, State Key Laboratory for Mechanical Behaviour of Materials, Xi’an Jiaotong University, Xi’an 710049, China
Authors to whom correspondence should be addressed.
Received: 29 November 2018 / Revised: 5 January 2019 / Accepted: 5 January 2019 / Published: 21 January 2019
(This article belongs to the Special Issue Visual Sensors)
PDF [2172 KB, uploaded 21 January 2019]


Image saliency detection is a very helpful step in many computer vision-based smart systems to reduce the computational complexity by only focusing on the salient parts of the image. Currently, the image saliency is detected through representation-based generative schemes, as these schemes are helpful for extracting the concise representations of the stimuli and to capture the high-level semantics in visual information with a small number of active coefficients. In this paper, we propose a novel framework for salient region detection that uses appearance-based and regression-based schemes. The framework segments the image and forms reconstructive dictionaries from four sides of the image. These side-specific dictionaries are further utilized to obtain the saliency maps of the sides. A unified version of these maps is subsequently employed by a representation-based model to obtain a contrast-based salient region map. The map is used to obtain two regression-based maps with LAB and RGB color features that are unified through the optimization-based method to achieve the final saliency map. Furthermore, the side-specific reconstructive dictionaries are extracted from the boundary and the background pixels, which are enriched with geometrical and visual information. The approach has been thoroughly evaluated on five datasets and compared with the seven most recent approaches. The simulation results reveal that our model performs favorably in comparison with the current saliency detection schemes. View Full-Text
Keywords: salient region detection; appearance based model; regression based model; human visual attention; background dictionary salient region detection; appearance based model; regression based model; human visual attention; background dictionary

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Fareed, M.M.S.; Chun, Q.; Ahmed, G.; Murtaza, A.; Asif, M.R.; Fareed, M.Z. Appearance-Based Salient Regions Detection Using Side-Specific Dictionaries. Sensors 2019, 19, 421.

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