Editing Content-based image retrieval (section)

===Texture===
[[Image texture|Texture]] measures look for visual patterns in images and how they are spatially defined.  Textures are represented by [[Texel (graphics)|texels]] which are then placed into a number of sets, depending on how many textures are detected in the image.  These sets not only define the texture, but also where in the image the texture is located.<ref name="Shapiro2001"/>

Texture is a difficult concept to represent. The identification of specific textures in an image is achieved primarily by modeling texture as a two-dimensional gray level variation. The relative brightness of pairs of pixels is computed such that degree of contrast, regularity, coarseness and directionality may be estimated.<ref name="Rui"/><ref name="Tamura">{{cite journal | last=Tamura| first=Hideyuki |author2=Mori, Shunji |author3=Yamawaki, Takashi | title=Textural Features Corresponding to Visual Perception | journal=IEEE Transactions on Systems, Man, and Cybernetics| year=1978|volume=8|issue=6|pages=460, 473 | doi=10.1109/tsmc.1978.4309999| s2cid=32197839 }}</ref> The problem is in identifying patterns of co-pixel variation and associating them with particular classes of textures such as ''silky'', or ''rough''.

Other methods of classifying textures include:
* [[Image texture#Co-occurrence Matrices|Co-occurrence matrix]]
* [[Image texture#Laws Texture Energy Measures|Laws texture energy]]
* [[Wavelet transform]]
* [[Orthogonal transform]]s (discrete Chebyshev moments)