MB+-Tree: An Index Structure for Content-Based Retrieval

Dao, Son; Yang, Qi; Vellaikal, Asha

doi:10.1007/978-1-4613-0463-0_11

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…The MB -tree is an extension of the standard B -tree from one dimension to multiple dimensions [11]. The structure and the insertion and deletion algorithms of MB -trees are very similar to those of B -trees.…”

Section: Multidimensional B -Treementioning

confidence: 99%

Techniques and data structures for efficient multimedia retrieval based on similarity

2002

IEEE Trans. Multimedia

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As more and more information is captured and stored in the digital form, many techniques and systems have been developed for indexing and retrieval of text documents, audio, images, and video. The retrieval is normally based on similarities between extracted feature vectors of the query and stored items. Feature vectors are usually multidimensional. When the number of stored objects and/or the number of dimensions of the feature vectors are large, it will be too slow to linearly search all stored feature vectors to find those that satisfy the query criteria. Techniques and data structures are thus required to organize feature vectors and manage the search process so that objects relevant to the query can be located quickly. This paper provides a survey of these techniques and data structures.Index Terms-Efficient search, multidimensional data structures, multimedia databases, multimedia indexing and retrieval.

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Section: Multidimensional B -Treementioning

confidence: 99%

Techniques and data structures for efficient multimedia retrieval based on similarity

2002

IEEE Trans. Multimedia

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“…Many multidimensional indexing structures have been proposed to improve the search efficiency [60][61][62][63][64][65][66][67][68][69][70][71][72][73]. As we have seen, many features are required to represent an object and each feature may need to represent multiple parameters.…”

Section: Indexing Structurementioning

confidence: 99%

Design issues of multimedia information indexing and retrieval systems

Lu¹

1999

Journal of Network and Computer Applications

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“…Of these data structures, some are based on the ideas of B + -and B-trees [11], which initially are for organizing 1D feature vectors or single valued keys of stored items, such as multidimensional B + -tree [9], while others perform feature searching and updating by "ordering" the multidimensional features either based on feature space partition and filtering, such as K-D tree [2], R-tree [34,17] and its variants, R * -tree [14], R + -tree [38], and TV-tree [23], or by similarity measuring [33]. Another data organization method is the grid file [28], by which an n-dimensional space is divided into equal-sized hypercubes with each hypercube containing zero or more feature vectors.…”

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confidence: 99%

FAST: Toward more effective and efficient image retrieval

Zhang

2005

Multimedia Systems

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This paper focuses on developing a Fast And Semantics-Tailored (FAST) image retrieval methodology. Specifically, the contributions of FAST methodology to the CBIR literature include: (1) development of a new indexing method based on fuzzy logic to incorporate color, texture, and shape information into a region-based approach to improving the retrieval effectiveness and robustness;(2) development of a new hierarchical indexing structure and the corresponding hierarchical, elimination-based A* retrieval (HEAR) algorithm to significantly improve the retrieval efficiency without sacrificing the retrieval effectiveness; it is shown that HEAR is guaranteed to deliver a logarithm search in the average case; (3) employment of user relevance feedback to tailor the effective retrieval to each user's individualized query preference through the novel indexing tree pruning (ITP) and adaptive region weight updating (ARWU) algorithms. Theoretical analysis and experimental evaluations show that FAST methodology holds great promise in delivering fast and semantics-tailored image retrieval in CBIR.

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MB+-Tree: An Index Structure for Content-Based Retrieval

Cited by 6 publications

References 9 publications

Techniques and data structures for efficient multimedia retrieval based on similarity

Techniques and data structures for efficient multimedia retrieval based on similarity

Design issues of multimedia information indexing and retrieval systems

FAST: Toward more effective and efficient image retrieval

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