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Indexing images with multiple regions

Petrakis Evripidis

Απλή Εγγραφή

URIhttp://purl.tuc.gr/dl/dias/0F7A012D-3D8D-4EDB-AB25-81CA7CD93E5F-
Αναγνωριστικόhttp://www.intelligence.tuc.gr/~petrakis/publications/petr01a.pdf-
Γλώσσαen-
ΤίτλοςIndexing images with multiple regionsen
ΔημιουργόςPetrakis Evripidisen
ΔημιουργόςΠετρακης Ευριπιδηςel
ΠερίληψηSimilarity indexing using Spatial Access Methods (SAMs) like e.g., R-trees, assumes that each data entity (or query) is represented by exactly one multidimensional point. However, for several applications, including indexing and retrieval of multimedia data like onedimensional signals and images, it is required that each data entity is represented by multiple pointsin a multidimensional space. This work extendsthe existing framework of indexing using SAMs to handle such data entities and has many desirable properties: For example, it provides index support for the two most common types of similarity queries, namely range and nearest neighbor (NN) queries, it returns exactly the same answers with the sequential scan method (only much faster) and, it works with any SAM and any data type. The effectiveness of the proposed approach is demonstrated using images with multiple regions.en
ΤύποςΠερίληψη Δημοσίευσης σε Συνέδριοel
ΤύποςConference Paper Abstracten
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-01-
Ημερομηνία Δημοσίευσης2001-
Βιβλιογραφική ΑναφοράGiannis Varelas, Paraskevi Raftopoulou, Euripides G.M. Petrakis, Evangelos E. Milios. ( 2005, Sep. ). Semantic Similarity Methods in WordNet and their Application to Information Retrieval on the Web. Presented at 7th ACM International Workshop on Web Information and Data Management (WIDM 2005). [Online]. Available:http://www.intelligence.tuc.gr/~petrakis/publications/petr01a.pdfen

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