Classification of solid textures using 3d mask patterns

Abstract

3D solid textures are important data for computer graphics applications because they are useful for synthesizing photo realistic patterns such as stone, smoke, water, clouds, fire, and wood. Unlike typical 2D textures, 3D solid textures are represented in voxel forms, which use three-dimensional coordinates. Various kinds of research have been conducted for pattern analysis of 2D textures to help development of computer applications. However, pattern analysis of 3D solid textures has not been investigated sufficiently even though 3D data related software is emerging. In this research, we have extended higher order local autocorrelation (HLAC) 2D mask patterns to 3D mask patterns so that pattern analysis software can handle not only 2D texture images but also 3D solid textures. Our experimental system can classify and look for 3D solid textures with similar patterns from a 3D solid texture database by using 3D HLAC masks. We have examined (1) similarity retrieval of 3D solid textures and (2) pattern classification of 3D solid textures by using the system.