Article
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A Unified Model for Salient Object Detection
Version 1
: Received: 20 April 2019 / Approved: 22 April 2019 / Online: 22 April 2019 (11:40:11 CEST)
How to cite: Alzahrani, A. J.; Afridi, H. A Unified Model for Salient Object Detection. Preprints 2019, 2019040244. https://doi.org/10.20944/preprints201904.0244.v1 Alzahrani, A. J.; Afridi, H. A Unified Model for Salient Object Detection. Preprints 2019, 2019040244. https://doi.org/10.20944/preprints201904.0244.v1
Abstract
We propose a novel method for salient object detection in different images. Our method integrates spatial features for efficient and robust representation to capture meaningful information about the salient objects. We then train a conditional random field (CRF) using the integrated features. The trained CRF model is then used to detect salient objects during the online testing stage. We perform experiments on two standard datasets and compare the performance of our method with different reference methods. Our experiments show that our method outperforms the compared methods in terms of precision, recall, and F-Measure.
Keywords
salient object; local binary pattern; histogram features; conditional random field
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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