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Selecting a Discriminant Subset of Co-occurrence Matrix Features for Texture-Based Image Retrieval

Najlae Idrissi1, 2 Contact Information, José Martinez1 and Driss AboutajdineContact Information

(1)  Atlas-GRIM, INRIA & LINA (FRE CNRS 2729) Polytechnic School of the University of Nantes BP 50609, 44306 Nantes cedex 03, France
(2)  GSCM Science Faculty of Rabat, University Mohamed V Rabat, Morocco
Abstract
In the general case, searching for images in a content-based image retrieval (CBIR) system amounts essentially, and unfortunately, to a sequential scan of the whole database. In order to accelerate this process, we want to generate summaries of the image database. In this paper, we focus on the selection of the texture features that will be used as a signature in our forthcoming system. We analysed the descriptors extracted from grey-level co-occurrence matrices’s (COM) under the constraints imposed by database systems.

Contact Information Najlae Idrissi
Email: prnom.nom@lina.univ-nantes.fr

Contact Information Driss Aboutajdine
Email: aboutaj@fsr.ac.ma
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