Texture based Markovian modelling for image retrieval

D. Benboudjema; F. Precioso

doi:10.1117/12.876710

2 March 2011 Texture based Markovian modelling for image retrieval

D. Benboudjema, F. Precioso

Proceedings Volume 7881, Multimedia on Mobile Devices 2011; and Multimedia Content Access: Algorithms and Systems V; 78811E (2011) https://doi.org/10.1117/12.876710
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

Texture is one of the main features with color, shape, edges ... by which human being perceives image. It can be viewed as a set of pixels within an image whose local statistics or local properties (e.g. periodicity, frequency) are constant or slightly varying. In this paper we address from the statistical standpoint, the image indexing problem for image retrieval. Two new Markov model based approaches allowing texture feature extraction will be proposed and a comparison to the texture features based on Gabor filters will be presented. The three methods have been tested for image retrieval task using SVM classifier with a Gaussian kernel on texture-oriented database, Brodatz, and on another texture database. The experimental results show for the proposed scheme promising results.

Citation Download Citation

D. Benboudjema and F. Precioso "Texture based Markovian modelling for image retrieval", Proc. SPIE 7881, Multimedia on Mobile Devices 2011; and Multimedia Content Access: Algorithms and Systems V, 78811E (2 March 2011); https://doi.org/10.1117/12.876710

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KEYWORDS

Image retrieval

Feature extraction

Databases

Filtering (signal processing)

Image processing

Modeling

Statistical analysis

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