3D Shape Representation Using Gaussian Curvature Co-occurrence Matrix

Co-occurrence matrix is traditionally used for the representation of texture information. In this paper, the co-occurrence matrix is combined with Gaussian curvature for 3D shape representation and a novel 3D shape description approach named Gaussian curvature co-occurrence matrix is proposed. Normalization process to Gaussian curvature co-occurrence matrix and the invariants independence of the translation, scaling and rotation transforms are demonstrated. Experiments indicate a better classification rate and running complexity to objects with slight different shape characteristic compared with traditional methods.