Texture Characteristics Parsing of Basic Stitch in Simulation Embroidery

Abstract

In order to fast identify and realistic simulate embroidery art, the respective texture characteristics of basic stitch in Simulation embroidery were extracted and preferred. Concretely, three feature extraction methods – gray co-occurrence matrix method (GLCM), Tamura method and gray difference statistics method (GDS), are combined to extract the features of embroidery needlework, and the best respected characteristics were compared and verified. Results shows that the best feature combination of needle texture in this paper is energy standard deviation, energy mean, standard deviation of moment of inertia, and mean of moment of inertia, which is defined as energy-moment of inertia feature. The proposed method effectively solves the inaccurate problem with single feature in the recognition of needle texture features, can be help for needlework recognition and virtual simulation.