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A Fast Orientation Estimation Approach of Natural Images

文献类型：期刊论文

作者Cao, Zhiqiang1; Liu, Xilong2; Gu, Nong3; Nahavandi, Saeid3; Xu, De2; Zhou, Chao1; Tan, Min1; xilong.liu
刊名IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
出版日期2016-11-01
卷号46期号:11页码:1589-1597
关键词Biological Simple Cell Differential Field Natural Image Orientation Estimation
DOI10.1109/TSMC.2015.2497253
文献子类Article
英文摘要This correspondence paper proposes a fast orientation estimation approach of natural images without the help of semantic information. Different from traditional low-level features, our low-level features are extracted inspired by the biological simple cells of the visual cortex. Two approximated receptive fields to mimic the biological cells are presented, and a local rotation operator is introduced to determine the optimal output and local orientation corresponding to an image position, which serve as the low-level feature employed in this paper. To generate the low-level features, a bisection method is applied to the first derivative of the model of receptive fields. Moreover, the feature screener is introduced to eliminate too much useless low-level features, which will speed up the processing time. After all the valuable low-level features are combined, the overall image orientation is estimated. The proposed approach possesses several features suitable for real-time applications. First, it avoids the tedious training procedure of some conventional methods. Second, no specific reference such as the horizon is assumed and no a priori knowledge of image is required. The proposed approach achieves a real-time orientation estimation of natural images using only low-level features with a satisfactory resolution. The effectiveness of our proposed approach is verified on real images with complex scenes and strong noises.
WOS关键词RECEPTIVE-FIELDS ; STRIATE CORTEX ; LOW-LEVEL ; FILTERS ; CELL
WOS研究方向Automation & Control Systems ; Computer Science
语种英语
WOS记录号WOS:000386225800010
资助机构National Natural Science Foundation of China(61273352 ; National High Technology Research and Development Program of China (863 Program)(2015AA042201) ; 61175111 ; 61421004 ; 61233014)
源URL[http://ir.ia.ac.cn/handle/173211/12137]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者xilong.liu
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Res Ctr Precis Sensing & Control, Inst Automat, Beijing 100190, Peoples R China
3.Deakin Univ, Ctr Intelligent Syst Res, Geelong, Vic 3217, Australia
推荐引用方式
GB/T 7714		 Cao, Zhiqiang,Liu, Xilong,Gu, Nong,et al. A Fast Orientation Estimation Approach of Natural Images[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2016,46(11):1589-1597.
APA Cao, Zhiqiang.,Liu, Xilong.,Gu, Nong.,Nahavandi, Saeid.,Xu, De.,...&xilong.liu.(2016).A Fast Orientation Estimation Approach of Natural Images.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,46(11),1589-1597.
MLA Cao, Zhiqiang,et al."A Fast Orientation Estimation Approach of Natural Images".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 46.11(2016):1589-1597.

入库方式： OAI收割

来源：自动化研究所

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