The first texture descriptors are proposed in 1973 by Haralick[1] and in 1975 by Marie Galloway[2] are still used today for image classification or segmentation in various domains. The majority of these features are defined for gray level images. Many papers have proposed different approaches among them, a parallel study of color and gray level texture characterization when other combined the two groups of features by defining joint features[3][4][5]. Combining features or defining them jointly are outperformed [6] even though these features impose some constraints such as the color system, measurement similarity methods. The aim of this paper is to use Clifford Algebra to represent multi-component images and to propose a color image texture.

An important storage capacity is necessary for the growing information need in images processing applications. But, some applications like cartography and electronic surveillance can tolerate little distortion of this information. Thus, quantization algorithms have been proposed to reduce memory space occupied and processing time. Our quantization algorithm is based on the criterion of colorimetric stationary state defined from the covariance matrix of a first order Markovian process. The colour space is divided iteratively into sub-cubes, each containing homogeneous colours obtained by the colorimetric stationary criterion. After division, the process continues by the creation of a colour palette with the number of colour being initially fixed by the operator. The value and originality of the method is demonstrated by applying it to different types of colour images.Index Terms: colour image analysis, first order stationary process matrix, 3D histogram, colour image quantization.