NDLI: Salient object detection via reliable boundary seeds and saliency refinement

Content Provider	IET Digital Library
Author	Wu, Xiyin Ma, Xiaodi Zhang, Jinxia Jin, Zhong
Abstract	Salient object detection can identify the most distinctive objects in a scene. In this study, a novel graph-based approach is proposed to detect a salient object via reliable boundary seeds and saliency refinement. A natural image is firstly mapped to a graph with superpixels as nodes. Saliency information is then diffused over the graph using seeds. For the reason that the boundary nodes may contain salient nodes, it is not appropriate to use all boundary nodes as the background seeds. Therefore, a boundary saliency measurement is proposed to obtain more accurate background seeds. After that, the information of background seeds is diffused by a two-stage scheme. A background-based map and a foreground-based map are generated based on the two-stage scheme. Furthermore, in order to enhance the detection accuracy, a refinement model is presented to fuse the information of background-based and foreground-based maps. Experiments on seven public datasets show the proposed algorithm out-performs the state-of-the-art salient object detection algorithms.
Starting Page	302
Ending Page	311
Page Count	10
ISSN	17519632
Volume Number	13
e-ISSN	17519640
Issue Number	Issue 3, Apr (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/13/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2018.5013
Journal	IET Computer Vision
Publisher Date	2018-10-24
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Accurate Background Seeds Background-based Map Boundary Nodes Boundary Saliency Measurement Combinatorial Mathematics Computer Vision And Image Processing Technique Detection Accuracy Detection Algorithm Distinctive Objects Feature Extraction Foreground-based Map Graph Theory Image Colour Analysis Image Segmentation Novel Graph-based Approach Object Detection Optical, Image And Video Signal Processing Refinement Model Reliable Boundary Seed Saliency Information Saliency Refinement Salient Node Salient Object Detection State-of-the-art Salient Two-stage Scheme
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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