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A Hierarchical Method for Clustering Binary Text Image

  • Yiguo Pu
  • Jinqiao Shi
  • Li Guo
Part of the Communications in Computer and Information Science book series (CCIS, volume 320)

Abstract

Image clustering is a crucial task in image retrieving, filtering and organizing. Most of recent work focuses on dealing with color images or gray scale images with features extracted from text content, annotation or image content. This paper aims at binary text images and proposes a novel clustering method that can be used for automatic image procession in digital library and automatic office. The method is divided into three main steps. Firstly images are preprocessed to denoise, correct orientation and produce coarse classes. Secondly, features are extracted and similar images are grouped into new classes with hierarchical clustering algorithm. At last new classes are combined to the nearest old ones under distance condition. To speed clustering Local Sensitive Hash algorithm is imported for boosting merging procedure. Experiments show that this method is faster and efficient compared with the basic clustering method.

Keywords

binary text image hierarchical cluster LSH 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yiguo Pu
    • 1
    • 2
    • 3
  • Jinqiao Shi
    • 1
    • 3
  • Li Guo
    • 1
    • 3
  1. 1.Institute of Information EngineeringCASChina
  2. 2.Graduate University, CASChina
  3. 3.Chinese National Engineering Laboratory for Information Security TechnologiesChina

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