摘要
伴随着计算机技术和互联网技术的快速发展,人类逐渐积累的数据量急剧增多。为了从海量的数据中挖掘出有用的信息,为用户提供决策支持,聚类算法得到了广泛的关注,并应用于各类数据处理与数据挖掘之中。本项目在分析图像视觉特性的基础之上,通过对图像颜色、纹理和形状多种特征信息的有效融合,利用K-均值算法进行聚类。提出的方法在采集的图像数据集上进行实验,有很好的聚类效果。
With the rapid development of computer technology and Intemet technology, the amount of data accumulated in the hu- man gradually increased dramatically. For the vast amounts of data into useful information for the user to provide decision sup- port, clustering algorithm has been widely attention and applied to all types of data processing and data mining applications. The project based on the analysis of visual features on the image, through the effective integration of color, texture and shape fea- tures of the image information, the use of K-Means algorithm to cluster. The proposed method can be carried out experiments on the acquired image data set, and has a good clustering effect.
作者
林青青
胡胜
郑灵凤
郭淑敏
朱蓉
LIN Qing-qing, HU Sheng, ZHENG Ling-feng ,GUO Shu-min, ZHU Rong （College of Mathematics Physics and Information Engineering, Jiaxing University, Jiaxing 314001, China）
出处
《电脑知识与技术》
2016年第11期164-167,共4页
Computer Knowledge and Technology
基金
浙江省自然基金项目（编号.LYl5F020039）
嘉兴学院国家级大学生创新创业训练计划项目（编号：201610354007）
浙江省大学生科技创新活动计划暨新苗人才计划（No.2015R417026）
关键词
数据处理
数据挖掘
特征提取
聚类分析
data processing
data mining
feature extraction
cluster analysis
