Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2014, Vol. 37 ›› Issue (s1): 60-65.doi: 10.13190/j.jbupt.2014.s1.012

• Papers • Previous Articles     Next Articles

Duplicate Image Detection Based on Two-Dimensional Cloud Model Filter

CHEN Ming1,2, WANG Shu-peng3, YUN Xiao-chun1,4, WU Guang-jun3   

  1. 1. National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. Zhengzhou University of Light Industry, Zhengzhou 450000, China;
    3. Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China;
    4. National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China
  • Received:2013-11-15 Online:2014-06-28 Published:2014-06-28
  • Supported by:
     

Abstract:

Because traditional duplicate image detection technologies can not ensure the scalability and the precision of image retrieval, this article proposes a duplicate image detection approach based on two-dimensional cloud model filter. On basis of bag-of-word model, the approach first maps the matching descriptors which are refined by Hamming embedding to points in the two-dimensional space, and then uses cloud model to compute the uncertainty of two-dimensional points' distribution for excluding the candidate images with larger fluctuation. Finally, the images are ranked according to voting score. Experiments show that the new approach not only maintains the merit of weak geometric consistency constraint algorithm which is suitable for large-scale image retrieval, but also significantly improves the accuracy of duplicate image detection.

Key words: Hamming embedding, weak geometric consistency constraint, bag-of-word, uncertainty, cloud model

CLC Number: