Similarity Retrieval of NOAA Satellite Imagery by Graph Matching

An attributed relational graph (ARG) is introduced into our NOAA satellite image database system. The node and the branch of an ARG denotes a classified region and a spatial relationship between adjacent regions respectively. Furthermore, a few attributes of a node / branch help to express numerical shape features of regions. Similarity retrieval thereby turns to be equivalent to graph matching. The similarity retrieval process of the system is as follows: 1) select a visual example image as a query and generate its graph structure, 2) calculate an optimal graph matching cost between a query graph and an archived graph in the database, utilizing algorithm A* with heuristic information, 3) choose archived images in the ascending order of a corresponding matching cost. The results of similarity retrieval experiments and their time complexity are presented. The method showed a better performance than simple template matching method.

Citation

Asanobu KITAMOTO, Changming ZHOU, Mikio TAKAGI, "Similarity Retrieval of NOAA Satellite Imagery by Graph Matching", Proceedings of the SPIE 1908 Image Storage and Retrieval Systems, pp. 60-73, 1993-01

BibTeX Format

@InProceedings{ kzt:spie93,
	author = {Asanobu KITAMOTO and Changming ZHOU and Mikio TAKAGI},
	title = {Similarity Retrieval of NOAA Satellite Imagery by Graph Matching},
	booktitle = {Proceedings of the SPIE 1908 Image Storage and Retrieval Systems},
	pages = {60-73},
	year = 1993,
	month = 01,
	note = {},
}

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