DocumentCode
411412
Title
IDA - iterative data analysis applied to color vector quantization
Author
D´Orazio, Tiziana ; Guaragnella, Cataldo
Author_Institution
Italian Nat. Res. Council, CNR, Bari, Italy
fYear
2004
fDate
2004
Firstpage
107
Lastpage
110
Abstract
An automatic iterative unsupervised data analysis tool is presented as a modification of well known Isodata algorithm. The main feature is its complete blindness and repeatability of the obtained results. It automatically selects a suitable number of features able to describe the whole data set requiring only one input parameter. As an application, color vector quantization has been addressed, both on real and on synthetic data sets, showing good performances.
Keywords
computer vision; data analysis; image coding; image colour analysis; image segmentation; iterative methods; multidimensional signal processing; vector quantisation; Isodata algorithm; automatic iterative unsupervised data analysis tool; color vector quantization; computer vision; data segmentation; multidimensional data processing; synthetic data sets; Blindness; Clustering algorithms; Color; Data analysis; Data mining; Data processing; Image segmentation; Iterative algorithms; Multidimensional systems; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Communications and Signal Processing, 2004. First International Symposium on
Print_ISBN
0-7803-8379-6
Type
conf
DOI
10.1109/ISCCSP.2004.1296230
Filename
1296230
Link To Document