Classification of sole patterns from a 3-Dimensional shoe model

摘要

The purpose of this paper is to classify the sole patterns from a 3D shoe model which is comprised of scattered point cloud data. Sole patterns can be divided into five categories based on the texture of each pattern. The point cloud data is sliced into a number of layers, and the unordered data points in each layer are projected onto a viewing plane to get a 2D shoeprint, in which we can further segment a texture element by region growing. Then, each texture element segmented can be classified into two types, non-closed curve and closed curve, by detecting if there are point cloud data in each external unit of the region and looking for the nearest points to the region. Finally, we can identify the type of the texture element into one of the five categories by analyzing its geometrical characteristics.