Interpreting image databases by region classification

This paper addresses automatic interpretation of images of outdoor scenes. The method allows instances of objects from a number of generic classes to be identified: vegetation, buildings, vehicles, roads, etc., thereby enabling image databases to be queried on scene content. The feature set is based, in part, on psychophysical principles and includes measures of colour, texture and shape. Using a large database of ground-truth labelled images, a neural network is trained as a pattern classifier. The method is demonstrated on a large test set to provide highly accurate image interpretations, with over 90% of the image area labelled correctly. (C) 1997 Pattern Recognition Society.