JOURNAL ARTICLE

Salient Object Detection Using Regional Contrast

Jin Zhan

Year: 2013 Journal:   Journal of Information and Computational Science Vol: 10 (16)Pages: 5103-5112   Publisher: Sun Yat-sen University

Abstract

Image saliency is an important visual character which offers a priority to decide which part of the image is to be selected. Salient object is the most saliency part in visual attention and is widely used in computer vision application. We propose a novel salient object detection method based on regional contrast. We connect salient edges to a shape contour by contour detection algorithm. These salient object contours are very important cues for saliency map evaluation. Then we extract salient regions from contours. The saliency map evaluation of regions simultaneously considers the contour integrality and spatial coherence of regions. On the basis of edge manipulation, our method is compact and simple that performs efficiently. Experimental results demonstrate that our method show better accuracy of salient object boundary and performs favorably against several state-of-the-art methods.

Keywords:
Contrast (vision) Computer science Salient Object (grammar) Computer vision Artificial intelligence

Metrics

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Cited By
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FWCI (Field Weighted Citation Impact)
19
Refs
0.22
Citation Normalized Percentile
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Topics

Visual Attention and Saliency Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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