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Texture Classification Using Dense Micro-Block Difference

Texture Classification Using Dense Micro-Block Difference

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 Texture Classification Using Dense Micro-Block Difference

 This paper is devoted to the problem of texture classification. Motivated by recent advancements in the field of compressive sensing and keypoints descriptors, a set of novel features called dense micro-block difference (DMD) is proposed. These features provide highly descriptive representation of image patches by densely capturing the granularities at multiple scales and orientations. Unlike most of the earlier work on local features, the DMD does not involve any quantization, thus retaining the complete information. We demonstrate that the DMD have dimensionality much lower than Scale Invariant Feature Transform (SIFT) and can be computed using integral image much faster than SIFT.


 


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  • Model: PROJ7008
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Monday 29 May, 2017.

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