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Intelligent line segment perception with cortex-like mechanisms

Version 2 2024-06-03, 22:35
Version 1 2016-03-11, 10:22
journal contribution
posted on 2024-06-03, 22:35 authored by X Liu, Z Cao, N Gu, S Nahavandi, C Zhou, M Tan
This 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: Systems

Volume

45

Pagination

1522-1534

Location

Piscataway, N.J.

ISSN

2168-2216

Language

eng

Publication classification

C Journal article, C1 Refereed article in a scholarly journal

Copyright notice

2015, IEEE

Issue

12

Publisher

IEEE