Abstract
In this paper, a simple and efficient method, based on Quaternionic Distance Based Weber Descriptor (QDWD) and object cues, is proposed for saliency detection. Firstly, QDWD, which was initially designed for detecting outliers in color images, is used to represent the directional cues in an image. Meanwhile, two low-level priors, namely the color contrast and center cue of the image, are utilized and fused as an object-level cue. Finally, by combining QDWD with object cues, a reliable saliency map of the image can be computed. Experimental results, based on a widely used and openly available database, show that the proposed method is able to produce promising results, compared to other state-of-the-art saliency-detection models.
Original language | English |
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Title of host publication | 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 |
Publisher | IEEE |
ISBN (Electronic) | 9789881476821 |
DOIs | |
Publication status | Published - 17 Jan 2017 |
Event | 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 - Jeju, Korea, Republic of Duration: 13 Dec 2016 → 16 Dec 2016 |
Conference
Conference | 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 |
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Country/Territory | Korea, Republic of |
City | Jeju |
Period | 13/12/16 → 16/12/16 |
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Information Systems
- Signal Processing