Invariant-based data model for image databases

We describe a new invariant-based data model for image databases under our approach for shape-based retrieval. The data model relies on contours description of the image shape, and emphasizes the use of invariants. Efficient indexing is based on geometric invariant features, while semi-local multi-valued invariant signatures are used for ranking the answers. The advantages of the proposed approach are its ability to retrieve images in situations in which part of the shape is missing (i.e., in case of occlusion or sketch queries), its ability to handle images distorted by different viewpoint transformations, and its ability to flexibly answer queries based on logical or shape descriptions (query by example), or on a combination of both. The approach also handles sketch based queries. We implemented our data model in an object oriented database system with a SQL-like user interface. The paper presents experimental results demonstrating the effectiveness of the proposed approach