Invariant texture segmentation via circular Gabor filter

Jianguo Zhang, Tieniu Tan, Li Ma

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    115 Citations (Scopus)

    Abstract

    In this paper, we focus on invariant texture segmentation, and propose a new method using circular Gabor filters (CGF) for rotation invariant texture segmentation. The traditional Gabor function is modified into a circular symmetric version. The rotation invariant texture features are achieved via the channel output of the CGF. A new scheme of the selection of Gabor parameters is also proposed for texture segmentation. Experiments show the efficacy of this method.
    Original languageEnglish
    Title of host publicationProceedings. 16th International Conference on Pattern Recognition 2002
    EditorsR. Kasturi, D. Laurendeau, C. Suen
    Place of PublicationCalifornia
    PublisherIEEE Computer Society
    Pages901-904
    Number of pages4
    Volume2
    ISBN (Print)076951695X
    DOIs
    Publication statusPublished - 2002
    Event16th International Conference on Pattern Recognition - Quebec, Canada
    Duration: 11 Aug 200215 Aug 2002
    http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8091

    Conference

    Conference16th International Conference on Pattern Recognition
    CountryCanada
    CityQuebec
    Period11/08/0215/08/02
    Internet address

    Fingerprint

    Gabor filters
    Textures
    Experiments

    Cite this

    Zhang, J., Tan, T., & Ma, L. (2002). Invariant texture segmentation via circular Gabor filter. In R. Kasturi, D. Laurendeau, & C. Suen (Eds.), Proceedings. 16th International Conference on Pattern Recognition 2002 (Vol. 2, pp. 901-904). California: IEEE Computer Society. https://doi.org/10.1109/ICPR.2002.1048450
    Zhang, Jianguo ; Tan, Tieniu ; Ma, Li. / Invariant texture segmentation via circular Gabor filter. Proceedings. 16th International Conference on Pattern Recognition 2002. editor / R. Kasturi ; D. Laurendeau ; C. Suen. Vol. 2 California : IEEE Computer Society, 2002. pp. 901-904
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    title = "Invariant texture segmentation via circular Gabor filter",
    abstract = "In this paper, we focus on invariant texture segmentation, and propose a new method using circular Gabor filters (CGF) for rotation invariant texture segmentation. The traditional Gabor function is modified into a circular symmetric version. The rotation invariant texture features are achieved via the channel output of the CGF. A new scheme of the selection of Gabor parameters is also proposed for texture segmentation. Experiments show the efficacy of this method.",
    author = "Jianguo Zhang and Tieniu Tan and Li Ma",
    year = "2002",
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    Zhang, J, Tan, T & Ma, L 2002, Invariant texture segmentation via circular Gabor filter. in R Kasturi, D Laurendeau & C Suen (eds), Proceedings. 16th International Conference on Pattern Recognition 2002. vol. 2, IEEE Computer Society, California, pp. 901-904, 16th International Conference on Pattern Recognition, Quebec, Canada, 11/08/02. https://doi.org/10.1109/ICPR.2002.1048450

    Invariant texture segmentation via circular Gabor filter. / Zhang, Jianguo; Tan, Tieniu; Ma, Li.

    Proceedings. 16th International Conference on Pattern Recognition 2002. ed. / R. Kasturi; D. Laurendeau; C. Suen. Vol. 2 California : IEEE Computer Society, 2002. p. 901-904.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    AB - In this paper, we focus on invariant texture segmentation, and propose a new method using circular Gabor filters (CGF) for rotation invariant texture segmentation. The traditional Gabor function is modified into a circular symmetric version. The rotation invariant texture features are achieved via the channel output of the CGF. A new scheme of the selection of Gabor parameters is also proposed for texture segmentation. Experiments show the efficacy of this method.

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    Zhang J, Tan T, Ma L. Invariant texture segmentation via circular Gabor filter. In Kasturi R, Laurendeau D, Suen C, editors, Proceedings. 16th International Conference on Pattern Recognition 2002. Vol. 2. California: IEEE Computer Society. 2002. p. 901-904 https://doi.org/10.1109/ICPR.2002.1048450