An Image Retrieval Method Based on a New Improved K-means Algorithm

MA Juan-juan; ZHANG Wei; LI Chao-feng; YANG Hong

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An Image Retrieval Method Based on a New Improved K-means Algorithm

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- An Image Retrieval Method Based on a New Improved K-means Algorithm
- Vol. 31, Issue 12, Pages: 148-151(2014)
- 作者机构：
  
  1. 江南大学物联网工程学院,江苏,无锡,214122
  2. 中国水产科学研究院机构淡水渔业研究中心,江苏,无锡,214081
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014
- 稿件说明：
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马娟娟, 张伟, 李朝锋, 杨弘. 新的改进K-means算法的图像检索方法[J]. 微电子学与计算机, 2014, 31(12): 148-151.

MA Juan-juan, ZHANG Wei, LI Chao-feng, et al. An Image Retrieval Method Based on a New Improved K-means Algorithm[J]. 2014, 31(12): 148-151.
马娟娟, 张伟, 李朝锋, 杨弘. 新的改进K-means算法的图像检索方法[J]. 微电子学与计算机, 2014, 31(12): 148-151. DOI：

MA Juan-juan, ZHANG Wei, LI Chao-feng, et al. An Image Retrieval Method Based on a New Improved K-means Algorithm[J]. 2014, 31(12): 148-151. DOI：

摘要

提出一种改进K-means算法的初始类心选取方法.首先基于HSV颜色空间计算样本图像和图像库中所有图像的特征向量

将样本图像的特征向量作为第一个初始类心

然后计算图像库所有图像距离样本图像的特征向量距离

找出距离最大的特征向量作为第二个初始类心

在剩下的特征向量中找到距离前两个初始类心和最大的特征向量作为第三个初始类心

依次类推确定剩下的初始类心

然后进行聚类

最后进行图像检索.实验结果论证了此算法的有效性.

Abstract

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.

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