An improved image segmentation algorithm for salient object detection

Liu, Yuee, Zhang, Jinglan, Tjondronegoro, Dian W., Geva, Shlomo, & Li, Zhengrong (2008) An improved image segmentation algorithm for salient object detection. In Proceedings of 23rd International Conference Image and Vision Computing, IEEE, Lincoln University, Christchurch.

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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.

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ID Code: 16835
Item Type: Conference Paper
Refereed: Yes
Keywords: semantic segmentation, salient object, JSEG, region merging
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2008 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 11 Dec 2008 01:44
Last Modified: 29 Feb 2012 13:46

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