Global-Context Based Salient Region Detection in Nature Images

Hong BAO  De XU  Yingjun TANG  

IEICE TRANSACTIONS on Information and Systems   Vol.E95-D   No.5   pp.1556-1559
Publication Date: 2012/05/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E95.D.1556
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
visual attention,  salient map,  global color context,  matrix decomposition,  

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Visually saliency detection provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. One of the main aims of visual attention in computer vision is to detect and segment the salient regions in an image. In this paper, we employ matrix decomposition to detect salient object in nature images. To efficiently eliminate high contrast noise regions in the background, we integrate global context information into saliency detection. Therefore, the most salient region can be easily selected as the one which is globally most isolated. The proposed approach intrinsically provides an alternative methodology to model attention with low implementation complexity. Experiments show that our approach achieves much better performance than that from the existing state-of-art methods.