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Pattern Analysis and Applications
Erschienen in: Pattern Analysis and Applications 4/2007

01.10.2007 | Theoretical Advances

Integrated color, texture and shape information for content-based image retrieval

verfasst von: Ryszard S. Choraś, Tomasz Andrysiak, Michał Choraś

Erschienen in: Pattern Analysis and Applications | Ausgabe 4/2007

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Abstract

Feature extraction and the use of the features as query terms are crucial problems in content-based image retrieval (CBIR) systems. The main focus in this paper is on integrated color, texture and shape extraction methods for CBIR. We have developed original CBIR methodology that uses Gabor filtration for determining the number of regions of interest (ROIs), in which fast and effective feature extraction is performed. In the ROIs extracted, texture features based on thresholded Gabor features, color features based on histograms, color moments in YUV space, and shape features based on Zernike moments are then calculated. The features presented proved to be efficient in determining similarity between images. Our system was tested on postage stamp images and Corel photo libraries and can be used in CBIR applications such as postal services.
Vorheriger Artikel Understanding people motion in video sequences using Voronoi diagrams
Nächster Artikel Binary object extraction using bi-directional self-organizing neural network (BDSONN) architecture with fuzzy context sensitive thresholding

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Metadaten
Titel
Integrated color, texture and shape information for content-based image retrieval
verfasst von
Ryszard S. Choraś
Tomasz Andrysiak
Michał Choraś
Publikationsdatum
01.10.2007
Verlag
Springer-Verlag
Erschienen in
Pattern Analysis and Applications / Ausgabe 4/2007
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-007-0071-0

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