3D shape retrieval focused on holes and surface roughness

Abstract

Although quite a few 3D shape descriptors have been proposed for more than a decade, 3D shape retrieval has remained a still challenging research. No single 3D shape descriptor has been known to outperform all the different types of 3D shape geometries. In this paper, we propose a new 3D shape descriptor that focuses on 3D mechanical parts having holes and surface roughness by using Fourier spectra computed from multiple projections of distinct images. Our proposed method makes it possible to explore potential real applications of 3D shape retrieval to manufacturing industries where the cost reduction of creating a new 3D shape from scratch is greatly appreciated. Our method explicitly attempts to extract holes and surface roughness, as well as contours, lines, and circular edges as our proposed features from multiple projections of a given 3D shape model, and use them to retrieve 3D shape objects. We demonstrate the effectiveness of our method by using several 3D shape benchmarks, one of which is composed of many mechanical parts, and compare our proposed method with several previously known methods. The results are very encouraging and promising.