DocumentCode
2495287
Title
An improved image segmentation algorithm for salient object detection
Author
Liu, Yuee ; Zhang, Jinglan ; Tjondronegoro, Dian ; Geva, Shlomo ; Li, Zhengrong
Author_Institution
Fac. of Inf. Technol., Queensland Univ. of Technol., Brisbane, QLD
fYear
2008
fDate
26-28 Nov. 2008
Firstpage
1
Lastpage
6
Abstract
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.
Keywords
image segmentation; object detection; image analysis; image segmentation; multiple region merging criteria; salient object detection; semantic object detection; Humans; Image color analysis; Image segmentation; Image texture analysis; Information technology; Layout; Merging; Object detection; Robustness; Shape; JSEG; region merging; salient object; semantic segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Vision Computing New Zealand, 2008. IVCNZ 2008. 23rd International Conference
Conference_Location
Christchurch
Print_ISBN
978-1-4244-3780-1
Electronic_ISBN
978-1-4244-2583-9
Type
conf
DOI
10.1109/IVCNZ.2008.4762141
Filename
4762141
Link To Document