• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2016, Vol. 38 ›› Issue (07): 1316-1321.

• 论文 • Previous Articles     Next Articles

A fast retrieval method for large scale images
based on multiple Hash algorithms  

TANG Xiaoman1,WANG Yunfei1,ZOU Fuhao1,ZHOU Ke2   

  1. (1.School of Computer Science and Technology,Huazhong University of Science and Technology,Wuhan 430074;
    2.Wuhan National Laboratory for Optoelectronics,Huazhong University of Science and Technology,Wuhan 430074,China)
  • Received:2015-12-05 Revised:2016-03-06 Online:2016-07-25 Published:2016-07-25

Abstract:

Hash technique is regarded as the most promising method of similarity search, which can be used in large scale multimedia data search. In order to solve the problem of low efficiency of data retrieval over large scale images, we propose a reverse index tree structure based on segmental Hash codes, and elaborate its implementation principles. In this structure, Hash codes are segmented. We design an inverted tree index structure for each section of Hash codes, and build the Hash index structure with the combination of the bloom filters. To further improve the accuracy of the retrieval results, we design a fusing algorithm which constructs the weighted undirected graph separately for the ranking results of multiple Hash algorithms. The fusion algorithm of the sorting list based on multiple Hash algorithms is described in detail by PageRank. Experimental results show that the structure of the inverted index tree based on segmental Hash codes can greatly improve data retrieval speed. Compared with the conventional single Hash algorithm sorting technique, the rank fusion technique for ordered lists of multiple Hash algorithms has obvious superiority in retrieval accuracy.

Key words: similarity search;Hash algorithm;reverse index trees;sort fusion algorithm