Fast color-spatial feature based image retrieval methods

Authors:
Chuen-Horng Lin;Der-Chen Huang;Yung-Kuan Chan;Kai-Hung Chen;Yen-Jen Chang
Affiliations:
Department of Information Science, National Taichung Institute of Technology, Taiwan, ROC;Department of Computer Science, National Chung Hsing University, Taiwan, ROC;Department of Management Information Systems, National Chung Hsing University, Taiwan, ROC;Department of Computer Science, National Chung Hsing University, Taiwan, ROC;Department of Computer Science, National Chung Hsing University, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

In this paper, three types of image features are proposed to describe the color and spatial distributions of an image. In these features, the K-means algorithm is adopted to classify all of the pixels in an image into several clusters according to their colors. By measuring the spatial distance among the pixels in a same cluster, the three types of color spatial distribution (CSD) features of the image is obtained. Based on the three types of CSD features, three image retrieval methods are also provided. To accelerate the image retrieval methods, a fast filter is also presented to eliminate most undesired images in advance. A genetic algorithm is also given to decide the most suitable parameters which are used in the proposed image retrieval methods. The proposed image retrieval methods are simple. Moreover, the experiments show that the proposed methods can provide impressive results as well.