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Lane detection by orientation and length discrimination.

Lane detection by orientation and length discrimination. Research Abstract Details 

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  • Lane detection by orientation and length discrimination. Abstract Text:

    a s laiA S Lai,n c yungN C Yung,

    This paper describes a novel lane detection algorithm for visual traffic surveillance applications under the auspice of intelligent transportation systems. Traditional lane detection methods for vehicle navigation typically use spatial masks to isolate instantaneous lane information from on-vehicle camera images. When surveillance is concerned, complete lane and multiple lane information is essential for tracking vehicles and monitoring lane change frequency from overhead cameras, where traditional methods become inadequate. The algorithm presented in this paper extracts complete multiple lane information by utilizing prominent orientation and length features of lane markings and curb structures to discriminate against other minor features. Essentially, edges are first extracted from the background of a traffic sequence, then thinned and approximated by straight lines. From the resulting set of straight lines, orientation and length discriminations are carried out three-dimensionally with the aid of two-dimensional (2-D) to three-dimensional (3-D) coordinate transformation and K-means clustering. By doing so, edges with strong orientation and length affinity are retained and clustered, while short and isolated edges are eliminated. Overall, the merits of this algorithm are as follows. First, it works well under practical visual surveillance conditions. Second, using K-means for clustering offers a robust approach. Third, the algorithm is efficient as it only requires one image frame to determine the road center lines. Fourth, it computes multiple lane information simultaneously. Fifth, the center lines determined are accurate enough for the intended application.

    Lane detection by orientation and length discrimination. Publishing Authors By Initials

    as laiAS Lai,nc yungNC Yung,

    For similar abstracts research abstracts see: abstracts research

    PUBMED ID PMID:

    MEDLINE DATE:

    Lane detection by orientation and length discrimination. Journal Published:

    PUBLICATION TYPE: Journal Article

    Journal: IEEE transactions on systems, man, and cybernetics

    VOLUME: 30

    Page Numbers: 539-48

    Journal Abbreviation:

    ISSN: 1083-4419

    DAY: 6

    MONTH: 02

    YEAR: 2000

    Lane detection by orientation and length discrimination. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 9890044

    Lane detection by orientation and length discrimination. Keywords Mesh Terms:

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    Grant and Affiliation Information for Lane detection by orientation and length discrimination.

    AFFILIATION: Lab. for Intelligent Transp. Syst. Res., Hong Kong Univ., Pokfulam.

    Country: United States

    United States Research PublicationUnited States Research Publication

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    MEDLINETA: IEEE Trans Syst Man Cybern B C

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