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

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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.

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Authors and Affiliations

  1. Image Processing Group, Institute of Telecommunications, UT&LS Bydgoszcz Kaliskiego 7, 85-976, Bydgoszcz, Poland

    Ryszard S. Choraś, Tomasz Andrysiak & Michał Choraś

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  1. Ryszard S. Choraś
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  2. Tomasz Andrysiak
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  3. Michał Choraś
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Correspondence to Ryszard S. Choraś.

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Choraś, R.S., Andrysiak, T. & Choraś, M. Integrated color, texture and shape information for content-based image retrieval. Pattern Anal Applic 10, 333–343 (2007). https://doi.org/10.1007/s10044-007-0071-0

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