计算机工程与应用2018，Vol.54Issue(3)：212-216,5.DOI:10.3778/j.issn.1002-8331.1608-0135
全局对比和背景先验驱动的显著目标检测
Salient objects detection method using global contrast and background priors
摘要
Abstract
In order to overcome the problems of imprecise in background extraction and weak ability of anti-background existed in traditional approaches of background priors, a salient object detection method using the global contrast and background priors is proposed in this paper. Firstly, the source image is segmented into a series of perceptually uniform super-pixels, a global-based saliency map is then calculated by contrasting global color and the foreground seed is collected. Sec-ondly, those superpixels with large difference are selected as the background seeds by comparing each boundary super-pixels with the foreground seeds, and the background-based map is then computed. Finally, based on the integration of background-based and global-based saliency map, a multi foci of interest Gaussian model is proposed to reduce back-ground and highlight salient region. Compared with 6 state-of the-art methods on publicly available benchmark datasets (MSRA-1000), the simulation results demonstrate that the salient object detection approach proposed in this paper per-forms more robustly in dealing with the complex boundary information and suppressing noise comparing with 6 conven-tional methods.关键词
全局对比/背景先验/超像素分割/显著目标Key words
global contrast/background priors/superpixel segmentation/salient object分类
信息技术与安全科学引用本文复制引用
邓晨,谢林柏..全局对比和背景先验驱动的显著目标检测[J].计算机工程与应用,2018,54(3):212-216,5.基金项目
国家自然科学基金(No.61374047,No.60973095). （No.61374047,No.60973095）
