• a klein-bottle-based dictionary for texture representation

    جزئیات بیشتر مقاله
    • تاریخ ارائه: 1392/07/24
    • تاریخ انتشار در تی پی بین: 1392/07/24
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    • شماره تماس دبیرخانه رویداد: -
    a natural object of study in texture representation and material classification is the probability density function, in pixel-value space, underlying the set of small patches from the given image. inspired by the fact that small n×n high-contrast patches from natural images in gray-scale accumulate with high density around a surface k⊂rn2 with the topology of a klein bottle (carlsson et al. international journal of computer vision 76(1):1–12, 2008), we present in this paper a novel framework for the estimation and representation of distributions around k , of patches from texture images. more specifically, we show that most n×n patches from a given image can be projected onto k yielding a finite sample s⊂k , whose underlying probability density function can be represented in terms of fourier-like coefficients, which in turn, can be estimated from s . we show that image rotation acts as a linear transformation at the level of the estimated coefficients, and use this to define a multi-scale rotation-invariant descriptor. we test it by classifying the materials in three popular data sets: the curet, uiuctex and kth-tips texture databases.

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