Preprint Article Version 1 This version is not peer-reviewed

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 (doi: 10.20944/preprints201904.0244.v1). Alzahrani, A.J.; Afridi, H. A Unified Model for Salient Object Detection. Preprints 2019, 2019040244 (doi: 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.

Subject Areas

salient object; local binary pattern; histogram features; conditional random field

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.