A Lane Extraction Algorithm Based on Fuzzy Set | Zendy

Yuxiu Bai | Zendy; Huanhuan Zheng | Zendy; Jian Zhou | Zendy; Dongmei Zhou | Zendy

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A Lane Extraction Algorithm Based on Fuzzy Set

Author(s) -

Yuxiu Bai,

Huanhuan Zheng,

Jian Zhou,

Dongmei Zhou

Publication year - 2021

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2021/9390778

Subject(s) - fuzzy logic , degree (music) , set (abstract data type) , computer science , artificial intelligence , extraction (chemistry) , fuzzy set , image (mathematics) , track (disk drive) , computer vision , pattern recognition (psychology) , algorithm , data mining , chemistry , physics , chromatography , acoustics , programming language , operating system

Lanes are difficult to be extracted completely. A lane extraction algorithm is proposed according to vehicle driving rules. Vehicles are moving constantly, so the foreground area and background area cannot be defined effectively in the image. Therefore, based on the theory of fuzzy set, multidimensional degree is used to judge the membership degree of target and foreground in order to extract the moving area accurately. Then, the logistic regression model is established to determine the moving vehicles. Finally, based on the vehicle track, the lane extraction is realized by regional growth. The results show that the proposed algorithm can extract the road effectively.

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