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Intelligent line segment perception with cortex-like mechanisms
journal contribution
posted on 2015-12-01, 00:00 authored by X Liu, Z Cao, Nong Gu, Saeid Nahavandi, C Zhou, M TanThis 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.
History
Journal
IEEE Transactions on Systems, Man, and Cybernetics: SystemsVolume
45Issue
12Pagination
1522 - 1534Publisher
IEEELocation
Piscataway, N.J.Publisher DOI
ISSN
2168-2216Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2015, IEEEUsage metrics
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No categories selectedKeywords
Science & TechnologyTechnologyAutomation & Control SystemsComputer Science, CyberneticsComputer ScienceArtificial cellsbiological visual cortexline segment perception (LSP)self-organizationPROBABILISTIC HOUGH TRANSFORMRECEPTIVE-FIELDSOBJECT RECOGNITIONSTRIATE CORTEXEDGE-DETECTIONRECONSTRUCTIONIMAGESCATHOUGH TRANSFORM
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