Signature-Based Indexing for Retrieval by Spatial Content in Large 2D-String Image Databases

Abstract

Image matching and content-based spatial similarity assessment based on the 2D-String image representation has been extensively studied. However, for large image databases, matching a query against every 2D-String has prohibitive cost. Indexing techniques are used to filter irrelevant images so that image matching algorithms can only focus on relevant ones. Current 2D-String indexing techniques are not efficient for handling large image databases. In this paper, the Two Signature Multi-Level Signature File (2SMLSF) is used as an efficient tree structure that encodes image information into two types of binary signatures. The 2SMLSF significantly reduces the storage requirements, responds to more types of queries, and its performance significantly improves over current techniques. For a simulated image databases of 131,072 images, a storage reduction of up to 35% and a querying performance improvement of up to 93% were achieved.KeywordsImage RetrievalQuery ProcessingImage DatabaseQuery ImageLeaf LevelThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.