According to the shortcomings of instability and low efficiency for K-means based image retrieval algorithm

this paper proposed an improved method to determine the initial class center of K-means clustering algorithm.Firstly

it uses HSV color space to calculate the feature vectors of sample image and all the images in the image database

and take the sample images feature vector as the first initial cluster center

then calculate the distances of feature vector between all the images in the image database and sample image

and take the feature vector which has biggest distance as the second initial cluster center

and take the remaining feature vector of the most far away from the two initial cluster centers as the third initial cluster center

and determine the other initial cluster centers in the same way.Finally

the clustering are done according to the initial cluster centers to finish image retrieval.Experimental results suggest the validity of the algorithm.