Image texture segmentation using polar S-transform and principal component analysis
    1.
    发明授权
    Image texture segmentation using polar S-transform and principal component analysis 有权
    使用极化S变换和主成分分析的图像纹理分割

    公开(公告)号:US07259767B2

    公开(公告)日:2007-08-21

    申请号:US11118366

    申请日:2005-05-02

    摘要: The present invention relates to a method and system for segmenting texture of multi-dimensional data indicative of a characteristic of an object. Received multi-dimensional data are transformed into second multi-dimensional data within a Stockwell domain based upon a polar S-transform of the multi-dimensional data. Principal component analysis is then applied to the second multi-dimensional data for generating texture data characterizing texture around each data point of the multi-dimensional data. Using a classification process the data points of the multi-dimensional data are partitioned into clusters based on the texture data. Finally, a texture map is produced based on the partitioned data points. The present invention provides image texture segmentation based on the polar S-transform having substantially reduced redundancy while keeping maximal data variation.

    摘要翻译: 本发明涉及用于分割指示对象的特征的多维数据的纹理的方法和系统。 基于多维数据的极化S变换,接收的多维数据被转换到Stockwell域内的第二多维数据。 然后将主成分分析应用于第二多维数据,用于生成在多维数据的每个数据点周围表征纹理的纹理数据。 使用分类处理,基于纹理数据将多维数据的数据点划分成簇。 最后,基于分区数据点产生纹理图。 本发明提供了基于极化S变换的图像纹理分割,其具有显着减少的冗余度,同时保持最大数据变化。

    Image texture segmentation using polar S-transform and principal component analysis
    2.
    发明申请
    Image texture segmentation using polar S-transform and principal component analysis 有权
    使用极化S变换和主成分分析的图像纹理分割

    公开(公告)号:US20050253863A1

    公开(公告)日:2005-11-17

    申请号:US11118366

    申请日:2005-05-02

    IPC分类号: G09G5/00

    摘要: The present invention relates to a method and system for segmenting texture of multi-dimensional data indicative of a characteristic of an object. Received multi-dimensional data are transformed into second multi-dimensional data within a Stockwell domain based upon a polar S-transform of the multi-dimensional data. Principal component analysis is then applied to the second multi-dimensional data for generating texture data characterizing texture around each data point of the multi-dimensional data. Using a classification process the data points of the multi-dimensional data are partitioned into clusters based on the texture data. Finally, a texture map is produced based on the partitioned data points. The present invention provides image texture segmentation based on the polar S-transform having substantially reduced redundancy while keeping maximal data variation.

    摘要翻译: 本发明涉及用于分割指示对象的特征的多维数据的纹理的方法和系统。 基于多维数据的极化S变换,接收的多维数据被转换到Stockwell域内的第二多维数据。 然后将主成分分析应用于第二多维数据,用于生成在多维数据的每个数据点周围表征纹理的纹理数据。 使用分类处理,基于纹理数据将多维数据的数据点划分成簇。 最后,基于分区数据点产生纹理图。 本发明提供了基于极化S变换的图像纹理分割,其具有显着减少的冗余度,同时保持最大数据变化。