ARTEX: A Self-organizing Architecture for Classifying Image Regions

A self-organizing architecture is developed for image region classification. The system consists of a preprocessor that utilizes multiscale filtering, competition, cooperation, and diffusion to compute a vector of image boundary and surface properties, notably texture and brightness properties. This vector inputs to a system that incrementally learns noisy multidimensional mappings and their probabilities. The architecture is applied to difficult real-world image classification problems, including classification of synthetic aperture radar and natural texture images, and outperforms a recent state-of-the-art system at classifying natural textures.