Texture analysis plays an important role in image analysis and pattern recognition

and texture description is a basic research topic of texture analysis. Though texture has not a uniform definition

it is acknowledged that neighborhood properties represent the dominant of a texture. Otherwise the distribution and spatial dependencies of local gray tones are periodic to homogeneous texture. So this local information can be used to describe a texture primitive

and it will work well for texture discrimination. A new texture descriptor is proposed based on the 8-neighbour gray tone spatial dependencies by using 8-neighbour Fourier series. The 8-neighbour of the point are treated as a periodic series

and their Fourier series are computed. Then the local Fourier coefficients map is generated from these local Fourier series of the whole image. A histogram of local Fourier series of the texture image was extracted by quantizing these Fourier coefficients as a texture descriptor. Because the quantization uses only the magnitudes of Fourier coefficients

this descriptor is shift-invariant and rotation-invariant. Experiments on 13 samples of Brodatz textures demonstrate the efficiency and effect of texture classification.