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Parallel Image Texture Feature Extraction under Hadoop Cloud Platform

  • HaoDong Zhu
  • Zhen Shen
  • Li Shang
  • XiaoPing Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8588)

Abstract

With the increasing amount of digital image data, massive image process and feature extraction process have become a time-consuming process. As an excellent mass data processing and storage capacity of the open source cloud platform, Hadoop provides a parallel computing model MapReduce, HDFS distributed file system module. Firstly, we introduced Hadoop platform programming framework and Tamura texture features. And then, the image processing and feature texture feature extraction calculations involved in the process to achieve Hadoop platform. The results which comparison with Matlab platform shows it is less obvious advantage of Hadoop platform in image processing and feature extraction of lower-resolution images, but for image processing and feature extraction of high-resolution images, the time spent in Hadoop platform is greatly reducing, data processing capability the advantages is obvious.

Keywords

Hadoop Tamura Texture Feature Image Processing Feature Extraction 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • HaoDong Zhu
    • 1
  • Zhen Shen
    • 1
  • Li Shang
    • 2
  • XiaoPing Zhang
    • 3
  1. 1.School of Computer and Communication EngineeringZhengZhou University of Light IndustryHenan ZhengzhouChina
  2. 2.Department of Communication Technology, College of Electronic Information EngineeringSuzhou Vocational UniversitySuzhouChina
  3. 3.College of Electronics and Information EngineeringTongji University ShanghaiChina

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