DocumentCode
2172823
Title
How to perform texture recognition from stochastic modeling in the wavelet domain
Author
Atto, Abdourrahmane M. ; Berthoumieu, Yannick
Author_Institution
Lab. IMS, Univ. de Bordeaux, Talence, France
fYear
2011
fDate
22-27 May 2011
Firstpage
4320
Lastpage
4323
Abstract
The paper addresses content-based image retrieval from texture data bases, by using stochastic modeling in the wavelet domain. It pro poses an analysis of the key parameters involved in such a content based texture retrieval. These parameters are the wavelet order and the goodness-of-fit measure used to select the best family of distributions for modeling the subband wavelet coefficients. It is shown that taking suitable parameters into consideration makes it possible to attain high retrieval rates in content-based texture retrieval.
Keywords
content-based retrieval; image recognition; image retrieval; image texture; stochastic processes; wavelet transforms; content based image retrieval; goodness-of-fit measure; stochastic modeling; subband wavelet coefficients; texture databases; texture recognition; wavelet domain; wavelet order; Computational modeling; Databases; Optical fibers; Stochastic processes; Wavelet packets; Similarity; Stochastic modeling; Texture; Wavelets;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location
Prague
ISSN
1520-6149
Print_ISBN
978-1-4577-0538-0
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2011.5947309
Filename
5947309
Link To Document