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Actualités de l'école

09/03/2016

Doctorate thesis defense of Amani CHAKER




Doctorate thesis defense on Monday 14 March 2016 at 09h00 ,in Amphi I at Sup’Com.


Entitled : Contributions à l’indexation d’image dans le domaine transformé en ondelettes

Presented by : Amani CHAKER 





Committee


President

Kais Ouni

Professor, ENICarthage, Tunisia.

 

 

 

Reporters

Frédéric Dufaux

CNRS Research Director at LTCI, Télécom ParisTech, France.

 

Azza Ould Zaid

Professor, ISI, Tunisia.

 

Examiner

Slim Mhiri

Associate Professor, ENSI.

 

Thesis Director

Amel Benazza

Professor, SUP’COM, Tunisia.


Abstract


this thesis addresses the problem of images indexing and retrieval in the wavelet transform domain. In particular, two major issues are considered: the indexing of stereo images and the impact of quantization in still image retrieval schemes.


In the first part, we propose novel retrieval approaches devoted to stereo images which integrate the disparity information with the visual contents of stereo images. In the first strategy, the two views are processed separately through a univariate model. An appropriate bivariate model is employed to exploit the cross-view dependencies in the second method. In the third strategy, we resort to a multivariate model to further capture the spatial dependencies of wavelet subbands.


In the second part, different strategies are designed to improve the drop of retrieval performances resulting from the quantization of database or query images. First, we propose to operate on the quantized coefficients by applying a processing step that aims at reducing the mismatch between the bitrates of the model and the query images. As an alternative, we propose to recover the statistical parameters of original wavelet coefficients directly from the quantized ones. Then, we investigate different quantization schemes and we exploit inherent properties of each one in order to design an efficient retrieval strategy.

Keywords


Content-based image retrieval, feature extraction, stereo pairs ,disparity map, image compression, transform domain, moment preserving quantization, distribution preserving quantization