Abstract
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. Color is one of the important features used in CBIR systems. The methods of characterizing color fall into two major categories:Â Histograms and Statistical. An experimental comparison of a number of different color features for content-based image retrieval presented in these paper. The primary goal is to determine which color feature is most efficient in representing the spatial distribution of images. In this paper, we analyze and evaluate both Statistical and Structural color features. For the experiments, publicly available image databases are used. Analysis and comparison of individual color features are presented
Highlights
Problems related to the image indexing and retrieval have extensively been studied during last severaldecades
Texture, and shape of objects are classified as general characteristics. They are used in the majority of Content-based image retrieval (CBIR) systems and are convenient for retrieval from heterogeneous image collections
All methods for representing color feature of an image can be classified into two groups: color histograms and statistical methods of color representation (Fig. 4).Quality of color feature vectors greatly dependsonthecolor space selection
Summary
Development of multidimensionalindexing algorithms to facilitate fastsearch in large-scale collections of high dimensiondataRetrieval system design. Texture, and shape of objects are classified as general characteristics They are used in the majority of CBIR systems and are convenient for retrieval from heterogeneous image collections. All methods for representing color feature of an image can be classified into two groups: color histograms and statistical methods of color representation (Fig. 4).Quality of color feature vectors greatly dependsonthecolor space selection. Reliable features are those comparison of which allows one to derive a correct conclusion regarding similarity of the corresponding images
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