Classification of scene photographs from local orientations features

Natural image understanding is a very active and promising research domain both in psychology for visual perception modelling and in computer science for image retrieval. In this study, we investigate the efficiency of orientation distributions over the whale image in the scale space. The global distribution of the local dominant orientations (LDO) appears to be a powerful feature for discriminating between four semantic categories of real world scenes (indoor scenes, urban scenes, open landscapes, closed landscapes). The selected optimal scale is compatible with psychological experiments and classification performances show that a global representation of dominant orientations is a simple, efficient and compact method for scene recognition. (C) 2000 Elsevier Science B.V. All rights reserved.