Using Three-Dimensional Features to Improve Terrain Classification

Texture has long been regarded as spatial distributions of gray-level variation, and texture analysis has generally been confined to the 2-D image domain. Introducing the concept of "3-D world texture", this paper considers texture as a function of 3-D structures and proposes a set of "3-D textural features". The proposed 3-D features appear to have a great potential in terrain classification. Experiments have been carried out to compare the 3-D features with a popular traditional 2-D feature set. The results show that the 3-D features significantly outperform the 2-D features in terms of classification accuracy. 1 Introduction Texture analysis is an important area in computer vision and has been extensively studied (e.g. [1, 2, 3, 4]). While it is widely accepted that texture has no formal and precise definition, it is generally presumed to be a spatial distributions of gray-level variations, or regular structural "patterns", in the image. This presumption has dominated texture anal..