Kao, C.-C.C.-C.KaoLai, J.-H.J.-H.LaiSHAO-YI CHIEN2018-09-102018-09-102011http://www.scopus.com/inward/record.url?eid=2-s2.0-80155131281&partnerID=MN8TOARShttp://scholars.lib.ntu.edu.tw/handle/123456789/365135Image segmentation is a well-developing topic in the image processing, and a number of previous works have been proposed and achieved high performance. However, most previous works needed user-assistance to provide the prior information of the target object in the segmentation. In this paper we propose an unsupervised scheme, combining the salient object detection and segmentation method, to segment the target object without any prior information from users. The experimental results show that the proposed salient color model derived with salient features can provide a prior information with high confidence to generate precise segmentation automatically. The proposed color model of salient objects can not only be applied with Min-Cut algorithm, but also extended to more segmentation algorithms, like matting or non-parametric model. © 2011 IEEE.Foreground Extraction; Graph Cuts; Image Editing; Image Segmentation; Salient Object ExtractionColor models; Foreground extraction; Graph Cuts; High confidence; Image editing; Min-cut algorithm; Non-parametric model; Object segmentation; Prior information; Salient features; Salient object detection; Salient objects; Segmentation algorithms; Segmentation methods; Target object; Algorithms; Color; Models; Image segmentationconference paper10.1109/ICME.2011.60119092-s2.0-80155131281