caa a22 4500 60544787X CHVBK 20210128100134.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s11042-014-1871-z doi (NATIONALLICENCE)springer-10.1007/s11042-014-1871-z An efficient segmentation method using saliency object detection [Elektronische Daten] [Chongbo Zhou, Chuancai Liu] Automatic co-segmentation is a challenging task because it lacks of prior cues. In this paper, an efficient region contrast based method is proposed for salient object detection and segmentation. The coarse location information of the salient object and the background is first estimated based on the distribution of the detected key-points. Histograms of the estimated foreground and background are calculated as their features. An image is then over-segmented into super-pixels and their histograms are computed. The saliency of a super-pixel is obtained according to the similarity coefficients between the super-pixel and the estimated foreground/background. With the saliency map, the salient object in the image is extracted using a graph cut based optimized framework. The proposed method is compared with state-of-the-art methods on the widely used dataset, and the experiments show that it overall obtains more accurate results. Springer Science+Business Media New York, 2014 Object segmentation nationallicence Saliency detection nationallicence Similarity measurement nationallicence Zhou Chongbo School of Computer Science and Engineering, Nanjing University of Science and Technology, 210094, Nanjing, Jiangsu, China aut Liu Chuancai School of Computer Science and Engineering, Nanjing University of Science and Technology, 210094, Nanjing, Jiangsu, China aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/15(2015-08-01), 5623-5634 1380-7501 74:15<5623 2015 74 11042 https://doi.org/10.1007/s11042-014-1871-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-014-1871-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhou Chongbo School of Computer Science and Engineering, Nanjing University of Science and Technology, 210094, Nanjing, Jiangsu, China aut NATIONALLICENCE 700 1- Liu Chuancai School of Computer Science and Engineering, Nanjing University of Science and Technology, 210094, Nanjing, Jiangsu, China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/15(2015-08-01), 5623-5634 1380-7501 74:15<5623 2015 74 11042