DocumentCode
2743224
Title
Successive approximation source coding and image enabled data mining
Author
Barnes, Christopher F.
Author_Institution
Georgia Inst. of Technol., Atlanta, GA, USA
fYear
2004
fDate
23-25 March 2004
Firstpage
525
Abstract
This paper deals with successive approximation source coding and image enabled data mining. Successive approximation source codes provide query returns consisting of sequences of aggregate data-tuples with image sets. A data mining statistical analysis or pattern search over a sequence of aggregates provides a sequence of data mining answers that is desirably fuzzy. Residual vector quantization (RVQ) provides a successive approximation source code with utility in image-enabled queries in image data mining tasks.
Keywords
data mining; image coding; image sequences; query processing; source coding; statistical analysis; vector quantisation; data-tuple sequence; image enabled data mining; image set; pattern search; query return; residual vector quantization; statistical analysis; successive approximation source coding; Aggregates; Algorithm design and analysis; Anthropometry; Cost accounting; Data mining; Data warehouses; Humans; Information analysis; Source coding; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Compression Conference, 2004. Proceedings. DCC 2004
ISSN
1068-0314
Print_ISBN
0-7695-2082-0
Type
conf
DOI
10.1109/DCC.2004.1281501
Filename
1281501
Link To Document