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Image Processing

Saliency detection using multiple region-based features

[+] Author Affiliations
Yinzhu Xue

Shanghai University, School of Communication and Information Engineering, Shanghai 200072, China

Zhi Liu

Shanghai University, School of Communication and Information Engineering, Shanghai 200072, China and Ministry of Education, Key Laboratory of Advanced Display and System Application, Shanghai 200072, China

Ran Shi

Shanghai University, School of Communication and Information Engineering, Shanghai 200072, China

Opt. Eng. 50(5), 057008 (May 19, 2011). doi:10.1117/1.3582338
History: Received October 19, 2010; Accepted April 04, 2011; Revised March 14, 2011; Published May 19, 2011; Online May 19, 2011
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This paper proposes a novel saliency model using multiple region-based features. The original image is initially segmented into a set of regions using the mean shift algorithm, and region merging is performed to obtain a moderate segmentation result. Then, three types of regional saliency measures are calculated using region-based features including local/global color difference, orientation difference, and spatial distribution, and they are integrated into an overall regional saliency measure for each region. Finally, the pixel-wise saliency map is generated by combining regional saliency measures with the distance-weighted color similarity between each pixel and each region. Experimental results demonstrate that our saliency model achieves an overall better saliency detection performance than previous saliency models, and the saliency maps generated using our model are more suitable for content-based applications such as salient object detection, content-aware image retargeting, and object-based image retrieval.

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© 2011 Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation

Yinzhu Xue ; Zhi Liu and Ran Shi
"Saliency detection using multiple region-based features", Opt. Eng. 50(5), 057008 (May 19, 2011). ; http://dx.doi.org/10.1117/1.3582338


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