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Evaluation of spatial similarity methods for image retrieval

Petrakis Evripidis, Kostas Georgiadis

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URIhttp://purl.tuc.gr/dl/dias/C3C066FA-3D37-4598-BEDF-AFB5C2235E2A-
Identifierhttp://www.intelligence.tuc.gr/~petrakis/publications/pege00.pdf-
Languageen-
TitleEvaluation of spatial similarity methods for image retrievalen
CreatorPetrakis Evripidisen
CreatorΠετρακης Ευριπιδηςel
CreatorKostas Georgiadisen
Content SummarySimilarity retrieval by spatial content (i.e., using multiple objects and their interelationships) in Image DataBases (IDBs) is still an open problem and has received considerable attention in the literature. In this work, we focus our attention on “queries by example” image and we study methods for answering such queries including the well accepted “editing distance” on Attributed Relational Graphs (ARGs) and the “Hungarian Method” for graph matching. We evaluate the time responses and the accuracy of these methods using a database of synthetic by realistic medical images. Our experiments indicate that the ARG editing distance, although the slowest, is the most accurate method.en
Type of ItemΑφίσα σε Συνέδριοel
Type of ItemConference Posteren
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-01-
Date of Publication2000-
Bibliographic CitationEuripides Petrakis and Kostas Georgiadis. (2000, Sept.). Evaluation of Spatial Similarity Methods for Image Retrieval. Presented at Signal Processing, Communications and Computer Science (CSCC' 2000). [Online].Available: http://www.intelligence.tuc.gr/~petrakis/publications/pege00.pdfen

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