Heuristic algorithms for similar configuration retrieval in spatial databases

Abstract. The search for similar configurations is an important research topic for content-based image retrieval in G.I.S. and spatial databases. Due to the complexity of the problem, finding the fittest solution in a large database is computationally intractable. Our work is focused on designing, implementing and experimentally evaluating two heuristic algorithms, an evolutionary and a hill-climbing one, that provide an approximate solution. With the use of spatial indexes we manage to efficiently deal with considerably large queries. We utilize a similarity framework that addresses topological, directional and distance relations. In this framework the problem of retrieving similar configurations is defined as a binary constraint satisfaction problem. Our work complements the existing work on similarity retrieval with two efficient, stochastic, algorithms.

Processing Fuzzy Spatial Queries: A Configuration Similarity Approach

. Increasing interest for configuration similarity is currently developing in the context of Digital Libraries, Spatial Databases and Geographical Information Systems. The corresponding queries retrieve all database configurations that match an input description (e.g., "find all configurations where an object x 0 is about 5km northeast of another x 1 , which, in turn, is inside object x 2 "). This paper introduces a framework for configuration similarity that takes into account all major types of spatial constraints (topological, direction, distance). We define appropriate fuzzy similarity measures for each type of constraint to provide flexibility and allow the system to capture real-life needs. Then we apply pre-processing techniques to explicate constraints in the query, and present algorithms that effectively solve the problem. Extensive experimental results demonstrate the applicability of our approach to images and queries of considerable size. 1. INTRODUCTION As opposed to visu..

On the retrieval of similar configurations

The search for similar configurations is an important research topic for content-based image retrieval in GISs and Spatial Databases. In the corresponding queries, the user imposes a set of spatial constraints among a set of objects asking for the images that best match these constraints. The paper defines configuration similarity using fuzzy measures and describes algorithms for retrieval from image databases. We distinguish three cases of query satisfiability: hard, where all the constraints of the query must be totally satisfied, soft, where some constraints may be (totally or partially) violated in solutions that are good on the average, and semi-hard, where each constraint must be at least partially satisfied. Although these problems are exponential in nature (NP-hard) we propose heuristics which, when combined with pre-processing strategies, yield good real-time performance even for large images and queries