Object-based image retrieval using hierarchical shape descriptor

Abstract

Shape is the most basic and convenient feature to describe objects. Retrieval by shape similarity is implemented in this project. Object shapes are segmented into tokens according to their local feature of minimum turn angle. User sketch is the query input and the retrieval algorithm matches the sketch with the nearest object in the database by using features distance. Scaling, rotation and missing sketch of objects are also considered in this paper. Together with the M-tree indexing, the system performance can be strengthened. However, many objects have similar outer shape boundary but different inner shapes. The retrieval accuracy will be affected by this situation. Hierarchical Shape Descriptor is proposed to solve the problem. It can distinguish similar outer boundaries but with different inner shapes objects. A completely new image retrieval system is implemented in order to accommodate the new image content descriptor. Our results show that the proposed system is fairly accurate and the Hierarchical Shape Descriptor is a better image content descriptor than the existing method using only the outer boundary.