Texture segmentation by multiscale aggregation of filter responses and shape elements

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Texture segmentation by multiscale aggregation of filter responses and shape elements (2003)

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by Meirav Galun , Eitan Sharon , Ronen Basri , Achi Brandt

Venue:	IN ICCV
Citations:	69 - 9 self

BibTeX

@INPROCEEDINGS{Galun03texturesegmentation,
    author = {Meirav Galun and Eitan Sharon and Ronen Basri and Achi Brandt},
    title = {Texture segmentation by multiscale aggregation of filter responses and shape elements},
    booktitle = {IN ICCV},
    year = {2003},
    pages = {716--723},
    publisher = {}
}

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Abstract

Texture segmentation is a difficult problem, as is apparent from camouflage pictures. A Textured region can contain texture elements of various sizes, each of which can itself be textured. We approach this problem using a bottom-up aggregation framework that combines structural characteristics of texture elements with filter responses. Our process adaptively identifies the shape of texture elements and characterize them by their size, aspect ratio, orientation, brightness, etc., and then uses various statistics of these properties to distinguish between different textures. At the same time our process uses the statistics of filter responses to characterize textures. In our process the shape measures and the filter responses crosstalk extensively. In addition, a top-down cleaning process is applied to avoid mixing the statistics of neighboring segments. We tested our algorithm on real images and demonstrate that it can accurately segment regions that contain challenging textures.

Keyphrases

filter response texture segmentation multiscale aggregation shape element texture element real image shape measure segment region different texture various size aspect ratio camouflage picture various statistic difficult problem bottom-up aggregation framework structural characteristic challenging texture textured region top-down cleaning process

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