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Proceedings Paper

Multiple images segmentation based on saliency map
Author(s): XiaoLan Ning; Cheng Xu; SiQi Li; ShiYing Li; ZhiQi Li
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Paper Abstract

Aiming at discovering and segmenting out common objects from multiple images, co-segmentation is a effective method. It is more accurate to make full use of the relationships between images in segmenting than only single image. The first step is to deal with single image with employing hierarchical segmentation to get a Contour Map, saliency detection to obtain the saliency map and object detection to find the possible common part. Then, constructing a digraph with the multiple local regions, and dealing with the digraph. When a digraph is constructed, the corresponding between adjacent two images is influential to the co-segmentation results. This paper develops a method to sort the images to co-segment. Also, we test the method on ICOSEG and MSRC datasets, and compare it with four proposed method. And the results show that it is efficient in co-segmentation with higher precision than many existing and conventional co-segmentation methods.

Paper Details

Date Published: 19 June 2017
PDF: 5 pages
Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104430N (19 June 2017); doi: 10.1117/12.2280275
Show Author Affiliations
XiaoLan Ning, Hunan Univ. (China)
Cheng Xu, Hunan Univ. (China)
SiQi Li, Hunan Univ. (China)
ShiYing Li, Hunan Univ. (China)
ZhiQi Li, Hunan Univ. (China)


Published in SPIE Proceedings Vol. 10443:
Second International Workshop on Pattern Recognition
Xudong Jiang; Masayuki Arai; Guojian Chen, Editor(s)

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