Construction of level of details in garment image skeleton

Abstract

Purpose – Skeleton plays an important role in representing the essential feature of garment in image. General skeleton extraction methods often yield many short skeletal branches. Though short branches reflect the geometric details of the garment, they are obstacles in extracting the essential features. The purpose of this paper is to provide an approach to hierarchically remove them to reveal the level of details (LOD) of the skeleton, thus both the essential skeleton and the geometric skeletal branches can be definitely extracted and separated. Design/methodology/approach – First, the initial garment image skeleton is extracted and smoothed. Then, the hierarchically removing mechanism is established on scoring the importance of each skeletal branch by an altered PageRank method and computing the symmetry among skeletal branches. Findings – Experimental examples show that this method can extract and separate garment essential skeleton as well as geometric skeletal branches hierarchically. Garments in same class have a similar essential skeleton with detailed differences, so this approach can be potentially applied in garment recognition and style specification. Originality/value – Traditionally, there is almost no work attempts to build LOD in skeleton of planar shapes. This paper provide an automatic device for building LOD skeleton for garment image. In another word, hierarchic skeletons with details in different prominence level are gradually established. And pairs of symmetric skeletal parts are found by taking advantage of symmetry characteristic of garment. This method is efficient in garment image skeleton extraction.