Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/24161
Title: Salient-region detection in a multi-level framework of image smoothing with over-segmentation
Authors: Gao, HY
Lam, KM 
Keywords: Image smoothing
Multi-level framework
Over-segmentation
Salient-region detection
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: 2014 IEEE International Conference on Image Processing, ICIP 2014, 2014, 7025667, p. 3297-3301 How to cite?
Abstract: Saliency detection is one of the extraordinary abilities of the human visual system; it also provides a powerful tool for predicting where people tend to focus in the free-viewing process. In this paper, we propose a novel salient-object detection method which applies an over-segmentation-based saliency detection algorithm to multi-level smoothed images. The original image is initially subjected to smoothing based on multi-level L0 gradient minimization; this can characterize its fundamental constituents while diminishing the insignificant details. Then, segment-based saliency computation is applied to the multi-level smoothed images to produce a series of intermediate saliency maps. The final saliency map is generated by combining the intermediate saliency maps. The proposed method is compared with six existing saliency models, and achieves the best performance in terms of Precision, Recall and F-measure, as well as in terms of the area under the ROC curve (AUC).
URI: http://hdl.handle.net/10397/24161
ISBN: 9.78E+12
DOI: 10.1109/ICIP.2014.7025667
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

69
Last Week
1
Last month
Checked on Nov 19, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.