Comparing global and interest point descriptors for similarity retrieval in remote sensed imagery
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Geographic image retrieval using interest point descriptors
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
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This paper presents a shape-based retrieval system and its application to infrared satellite images. A complete system is presented, from region extraction of a full hemisphere scan to the actual retrieval mechanism. After region extraction, polygonal approximation is applied to the region shape, and local features of the polygons are hashed to provide an association space. This space becomes the indexing structure through which retrieval takes place. Although the indexing stage, containing region extraction and polygonal approximation, is slow, the actual retrieval is very fast. On average, retrieval of a query shape from a database of 1965 shapes takes 0.7 seconds for the more reduced representation, and 2.8 seconds for the less reduced representation consisting of 1914 shapes. The overall design is good for a moderately sized database, and extensions could be made to apply the method to a massive database. The results show that the approach performs well, and that there is a substantial speed benefit for using the local association hashing method.