Application study of improved k-means clustering algorithm in image retrieval

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (10): 193-196.

• 图形、图像、模式识别 • Previous Articles Next Articles

Application study of improved k-means clustering algorithm in image retrieval

SHI Xiyun，XUE Anrong，LIU Yanhong

School of Computer Science & Telecommunications Engineering，Jiangsu University，Zhenjiang，Jiangsu 212013，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-04-01 Published:2011-04-01

改进k-means聚类算法在图像检索中的应用研究

史习云，薛安荣，刘艳红

江苏大学计算机科学与通信工程学院，江苏镇江 212013

Abstract

Abstract: In order to quickly and correctly retrieve the desired image from a large image database，a method combining the image feature index library and the average area histogram is presented.Adopting the image feature index database，it can reduce the number of visiting to the image database，and achieve fast retrieval.Using the average size histogram，it enhances the ability of distinguishing the spatial differences，which makes the search results better matching the human visual experience.The experimental results also show that the proposed method improves the speed and accuracy of image retrieval.

Key words: image retrieval, feature-index database, average area histogram, color spatial information

摘要： 为了从大规模图像数据库中快速而准确地检索到所需图像，提出了一种结合图像特征索引库和平均面积直方图的方法。通过图像特征索引库减少对图像数据库的访问次数和访问数据量，实现对图像的快速检索。使用平均面积直方图方法，增强算法区分空间差异的能力，使得检索结果与人的视觉感受更加吻合。实验结果亦表明，该方法提高了图像检索的速度和精度。

关键词: 图像检索, 特征索引库, 平均面积直方图, 颜色空间分布信息

SHI Xiyun，XUE Anrong，LIU Yanhong. Application study of improved k-means clustering algorithm in image retrieval[J]. Computer Engineering and Applications, 2011, 47(10): 193-196.

史习云，薛安荣，刘艳红. 改进k-means聚类算法在图像检索中的应用研究[J]. 计算机工程与应用, 2011, 47(10): 193-196.

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Application study of improved k-means clustering algorithm in image retrieval

改进k-means聚类算法在图像检索中的应用研究

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