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Color image retrieval and classification using fuzzy similarity measure and fuzzy clustering method

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3 Author(s)

Color image retrieval and classification are very important in the field of image processing. In this paper, we propose a method which is in token of color characteristic of one image using hue and thereby is used to calculate similarity between two pictures. We also take F-Stat. Measure to find the best threshold so that we can realize fuzzy partition, and finally fuzzy c-means algorithm is used to do image classification and the calculation of subjection degree of one picture in the corresponding class. The corresponding mathematical model is established. Also, we construct a frame in which image comparability is obtained through fuzzy similarity measure based on hue feature vector of image, thus image retrieval is finished, and image classification is realized by fuzzy clustering. The comparison of image retrieval result between RGB feature vector and only-hue feature vector in token of image characteristic is taken. The experiment shows that the idea which takes this fuzzy similarity measure and fuzzy clustering method as the scheme of image retrieval and classification is reasonable and effective.

Published in:

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Date of Conference:

15-18 Dec. 2009