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Intelligent Line Segment Perception With Cortex-Like Mechanisms
Liu, Xilong1,2; Cao, Zhiqiang1; Gu, Nong3; Nahavandi, Saeid3; Zhou, Chao1; Tan, Min1
Source PublicationIEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
2015-12-01
Volume45Issue:12Pages:1522-1534
SubtypeArticle
AbstractThis paper proposes a novel general framework for line segment perception, which is motivated by a biological visual cortex, and requires no parameter tuning. In this framework, we design a model to approximate receptive fields of simple cells. More importantly, the structure of biological orientation columns is imitated by organizing artificial complex and hypercomplex cells with the same orientation into independent arrays. Besides, an interaction mechanism is implemented by a set of self-organization rules. Enlightened by the visual topological theory, the outputs of these artificial cells are integrated to generate line segments that can describe nonlocal structural information of images. Each line segment is evaluated quantitatively by its significance. The computation complexity is also analyzed. The proposed method is tested and compared to state-of-the-art algorithms on real images with complex scenes and strong noises. The experiments demonstrate that our method outperforms the existing methods in the balance between conciseness and completeness.
KeywordArtificial Cells Biological Visual Cortex Line Segment Perception (Lsp) Self-organization
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TSMC.2015.2415764
WOS KeywordPROBABILISTIC HOUGH TRANSFORM ; RECEPTIVE-FIELDS ; OBJECT RECOGNITION ; STRIATE CORTEX ; EDGE-DETECTION ; RECONSTRUCTION ; IMAGES ; CAT
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61273352 ; National High Technology Research and Development Program of China (863 Program)(2015AA042201) ; 61175111 ; 61421004 ; 61273337 ; 60805038)
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000366891300005
Citation statistics
Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10649
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
3.Deakin Univ, Ctr Intelligent Syst Res, Geelong, Vic 3217, Australia
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences;  Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Liu, Xilong,Cao, Zhiqiang,Gu, Nong,et al. Intelligent Line Segment Perception With Cortex-Like Mechanisms[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2015,45(12):1522-1534.
APA Liu, Xilong,Cao, Zhiqiang,Gu, Nong,Nahavandi, Saeid,Zhou, Chao,&Tan, Min.(2015).Intelligent Line Segment Perception With Cortex-Like Mechanisms.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,45(12),1522-1534.
MLA Liu, Xilong,et al."Intelligent Line Segment Perception With Cortex-Like Mechanisms".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 45.12(2015):1522-1534.
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