Texture analysis with the Volterra model using conjugate gradient optimisation

Texture is an important characteristic di erentiating objects or regions of interest in an image. A variety of approaches to texture analysis has previously been proposed; the approach in this paper is from the stochastic eld, whereby a two-dimensional Volterra model is used to represent a texture eld. Statistical moments are introduced as a means of determining the Volterra model generator for an unknown texture, with a view to using this model subsequently for recognition. However, an overdetermined set of equations results. These can be solved in the least squares sense using a conjugate gradient descent method with multiple restarts.