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An improved image segmentation algorithm for salient object detection

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5 Author(s)
Yuee Liu ; Faculty of Information Technology, Queensland University of Technology, Australia ; Jinglan Zhang ; Dian Tjondronegoro ; Shlomo Geva
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Semantic object detection is one of the most important and challenging problems in image analysis. Segmentation is an optimal approach to detect salient objects, but often fails to generate meaningful regions due to over-segmentation. This paper presents an improved semantic segmentation approach which is based on JSEG algorithm and utilizes multiple region merging criteria. The experimental results demonstrate that the proposed algorithm is encouraging and effective in salient object detection.

Published in:

2008 23rd International Conference Image and Vision Computing New Zealand

Date of Conference:

26-28 Nov. 2008