Query Quality Refinement in Singular Value Decomposition to Improve Genetic Algorithms for Multimedia Data Retrieval

Simple item page
dc.contributor.authorCheruiyot, Wilson
dc.contributor.authorTan, Guanzheng
dc.contributor.authorMusau, Felix
dc.contributor.authorMushi, Joseph C.
dc.date.accessioned2016-07-25T16:31:25Z
dc.date.available2016-07-25T16:31:25Z
dc.date.issued2011-11
dc.description.abstractWith the development of internet and availability of multimedia data capturing devices, the size of Multimedia Digital Database (MDD) collection is increasing rapidly. The complex data presented by such systems do not have the total ordering property presented by the traditional data handled by Database Management Systems (DBMSs). The quality of the search experience in such systems is also normally a big challenge since users from various domains require efficient data searching, browsing and retrieval tools. This has triggered an important research topic in Multimedia information retrieval concerning effi- cient and effective image similarity search. Modern search algorithms are fast and effective on a wide range of problems, but on MDD with a large number of parameters and observations, manipulations of large matrices, storage and retrieval of large amounts of information may render an otherwise useful method slow or inoperable. The focus of this work is the application of image enhancement technique, using histogram equalization, to the images retrieved using singular value decomposition (SVD). SVD is a linear algebra technique used for discovering correlations within data. The approach, herein referred to as query quality refinement (QQR) technique, improves the image similarity search result, and when incorporated with genetic algorithms further optimizes the search. These beneficial applications can be extended to other different types of multimedia data in various areas such as the P2P and WiMAX networks.en_US
dc.identifier.citationCheruiyot, W., Tan, G.Z., Musau, F. and Mushi, J.C., 2011. Query quality refinement in singular value decomposition to improve genetic algorithms for multimedia data retrieval. Multimedia systems, 17(6), pp.507-521.en_US
dc.identifier.doi10.1007/s00530-011-0231-3
dc.identifier.urihttp://hdl.handle.net/20.500.11810/3425
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectMultimedia Digital Databaseen_US
dc.subjectSingular value decompositionen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMultimedia information retrievalen_US
dc.subjectQuery quality refinementen_US
dc.titleQuery Quality Refinement in Singular Value Decomposition to Improve Genetic Algorithms for Multimedia Data Retrievalen_US
dc.typeJournal Article, Peer Revieweden_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Query quality refinement in singular value decomposition to improve genetic algorithms for multimedia data retrieval.pdf
Size:
2.97 MB
Format:
Adobe Portable Document Format
Description:
Full text
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Department of Computer Science and Engineering