计算机与现代化 ›› 2013, Vol. 1 ›› Issue (2): 15-18.doi: 10.3969/j.issn.1006-2475.2013.02.004

• 图像处理 • 上一篇    下一篇

图像聚类的并行化

曹 磊,程建来   

  1. 天津大学软件学院,天津300072
  • 收稿日期:2012-10-11 修回日期:1900-01-01 出版日期:2013-02-27 发布日期:2013-02-27

Parallelization of Image Clustering

CAO Lei, CHENG Jian-la   

  1. School of Computer Software, Tianjin University, Tianjin 300072, China
  • Received:2012-10-11 Revised:1900-01-01 Online:2013-02-27 Published:2013-02-27

摘要: 随着科技进步,包括网络图片和视频监控在内的图像数据出现了迅速的增长。如何有效管理图像数据成为一个挑战。图像聚类是图像数据管理的重要一环。本文实现Hadoop平台下尺度不变特征转换算法(Scale Invariant Feature Transform, SIFT)和K-means聚类的MapReduce并行化,并且取得不错的效果。

关键词: 并行化, 图像聚类

Abstract: As technology advances, image data is rapidly growing including images and videos on Internet. How to effectively manage the image data is a great challenge. Image clustering is an important image data managing solution. This paper proposes a solution of MapReduce parallelization about the SIFT image feature extraction and K-means clustering method on Hadoop platform. It achieves good results.

Key words: parallelization, image clustering