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ICMCS
2010
IEEE

Saliency detection: A self-ordinal resemblance approach

12 years 5 days ago
Saliency detection: A self-ordinal resemblance approach
In saliency detection, regions attracting visual attention need to be highlighted while effectively suppressing non-salient regions for the semantic scene understanding. However, most previous methods tend to fail in suppressing highly textured backgrounds and also high contrast edges belonging to the non-salient regions. To address this problem, we propose a method for detecting salient regions based on a self-ordinal resemblance measure (SORM). Our saliency map is defined by using the center-surround computations based on the ordinal signatures obtained from local regions centered at each pixel. It can be regarded as an energy map and thus extended to image retargeting. Our approach is fully automatic and nonparametric. To justify robustness of our approach, the proposed method is compared with the state of the art methods on various images.1 Keywords— Saliency detection, visual attention, selfordinal resemblance, energy map
Wonjun Kim, Chanho Jung, Changick Kim
Added 26 Jan 2011
Updated 26 Jan 2011
Type Journal
Year 2010
Where ICMCS
Authors Wonjun Kim, Chanho Jung, Changick Kim
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