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题名: A Fast Orientation Estimation Approach of Natural Images
作者: Cao, Zhiqiang1; Liu, Xilong2; Gu, Nong3; Nahavandi, Saeid3; Xu De(徐德)2; Zhou, Chao1; Tan Min(谭民)1
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
DOI: 10.1109/TSMC.2015.2497253
通讯作者: xilong.liu
文章类型: 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标题词: Science & Technology ; Technology
类目[WOS]: Automation & Control Systems ; Computer Science, Cybernetics
研究领域[WOS]: Automation & Control Systems ; Computer Science
关键词[WOS]: RECEPTIVE-FIELDS ; STRIATE CORTEX ; LOW-LEVEL ; FILTERS ; CELL
收录类别: SCI
项目资助者: National Natural Science Foundation of China(61273352 ; National High Technology Research and Development Program of China (863 Program)(2015AA042201) ; 61175111 ; 61421004 ; 61233014)
语种: 英语
WOS记录号: WOS:000386225800010
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.ia.ac.cn/handle/173211/12137
Appears in Collections:精密感知与控制研究中心_期刊论文

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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

Recommended Citation:
Liu XL. A Fast Orientation Estimation Approach of Natural Images[J]. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS,2015(2015):1-9.
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