ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Similarity retrieval of iconic image database
Pattern Recognition
Retrieval of similar pictures on pictorial databases
Pattern Recognition
Design and evaluation of algorithms for image retrieval by spatial similarity
ACM Transactions on Information Systems (TOIS)
S-tree: a dynamic balanced signature index for office retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
A robust framework for content-based retrieval by spatial similarity in image databases
ACM Transactions on Information Systems (TOIS)
Efficient content-based indexing of large image databases
ACM Transactions on Information Systems (TOIS)
Signature files: an access method for documents and its analytical performance evaluation
ACM Transactions on Information Systems (TOIS)
Efficient Signature File Methods for Text Retrieval
IEEE Transactions on Knowledge and Data Engineering
Automated segmentation of brain MR images
Pattern Recognition
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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.