An improved image segmentation algorithm for salient object detection
- Resource Type
- Conference
- Authors
- Liu, Yuee; Zhang, Jinglan; Tjondronegoro, Dian; Geva, Shlomo; Li, Zhengrong
- Source
- 2008 23rd International Conference Image and Vision Computing New Zealand Image and Vision Computing New Zealand, 2008. IVCNZ 2008. 23rd International Conference. :1-6 Nov, 2008
- Subject
- Signal Processing and Analysis
Computing and Processing
Bioengineering
Image segmentation
Object detection
Merging
Humans
Shape
Layout
Robustness
Information technology
Image color analysis
Image texture analysis
semantic segmentation
salient object
JSEG
region merging
- Language
- ISSN
- 2151-2191
2151-2205
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.