Texture is one of the most important characteristics used in computer vision and image processing applications. In this paper, a new texture classification and retrieval method is proposed for texture analysis applications. The technique makes use of the random neural network model. The main aim is to represent textures with parameters which are the random neural network weights and classify and retrieve textures using this texture definition. The net work has neurons that correspond to each image pixel, and the neurons are connected according to neighboring relationship between pixels. The method is tested on images produced by using Brodatz album and texture blocks cut from remotely sensed imagery.