Programming and Computer Software

, Volume 35, Issue 3, pp 158–180 | Cite as

Content-based image retrieval methods

  • N. S. Vassilieva


Creation of a content-based image retrieval system implies solving a number of difficult problems, including analysis of low-level image features and construction of feature vectors, multidimensional indexing, design of user interface, and data visualization. Quality of a retrieval system depends, first of all, on the feature vectors used, which describe image content. The paper presents a survey of common feature extraction and representation techniques and metrics of the corresponding feature spaces. Color, texture, and shape features are considered. A detailed classification of the currently known features’ representations is given. Experimental results on efficiency comparison of various methods for representing and comparing image content as applied to the retrieval and classification tasks are presented.


Feature Vector Image Retrieval Medial Axis Color Histogram Zernike Moment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Pleiades Publishing, Ltd. 2009

Authors and Affiliations

  1. 1.HP Labs RussiaSt. PetersburgRussia

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