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
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;
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
DOI :
10.1109/IVCNZ.2008.4762141