文献类型：期刊文献

英文题名：Structure extraction and region contrast based salient object detection

作者：Zhang, Qing[1]; Lin, Jiajun[2]; Xie, Zhigang[3]

机构：[1] College of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, 201418, China; [2] Institute of Automation, East China University of Science and Technology, Shanghai, 200237, China; [3] Chengdu Watertek Information Technology Co. Ltd, Chengdu, 610041, China

年份：2016

卷号：10033

外文期刊名：Proceedings of SPIE - The International Society for Optical Engineering

收录：EI(收录号：20164903101477)

语种：英文

外文关键词：Extraction - Object recognition - Image segmentation - Benchmarking - Behavioral research

摘要：In this paper, we propose a novel salient object detection approach, which aims in suppressing distractions caused by the small scale pattern in the background and foreground. First, we employ a structure extraction algorithm as a preprocessing step to smooth the textures, eliminate high frequency components and retain the image's main structure information. Second, we segment the texture maps are computed and fused according to the color contrast and center prior cues. To better exploit each pixel's color and position information, we refine the fused saliency map. Experiments on two popular benchmark datasets demonstrate that our proposed approach achieves state-of-the-art performance compared with sixteen other state-of-the-art methods in terms of three popular evaluation measures, i.e., Precision and Recall curve, Area Under ROC Curve and F-measure value. ? 2016 SPIE.