Feature aggregating hashing for image copy detection

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• 作者：Lingyu Yan ; Fuhao Zou ; Rui Guo ; Lianli Gao ; Ke Zhou ; Chunzhi Wang
• 关键词：Image copy detection ; Visual words ; Feature aggregation ; Machine learning base hashing
• 刊名：World Wide Web
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：19
• 期：2
• 页码：217-229
• 全文大小：1,151 KB
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• 作者单位：Lingyu Yan (1)
  Fuhao Zou (2)
  Rui Guo (3)
  Lianli Gao (4)
  Ke Zhou (5)
  Chunzhi Wang (1)
  
  1. School of Computer Science, Hubei University of Technology, Wuhan, China
  2. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
  3. School of Computer, Southeast University, Nanjing, China
  4. School of Computer, University of Electronic Science and Technology of China, Hefei, China
  5. Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
  
• 刊物类别：Computer Science
• 刊物主题：Information Systems Applications and The Internet
  Database Management
  Operating Systems
  
• 出版者：Springer Netherlands
• ISSN：1573-1413

文摘

Currently, research on content based image copy detection mainly focuses on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very time-consuming and unscalable. Hence, we need to pay much attention to the efficiency of image detection. In this paper, we propose a fast feature aggregating method for image copy detection which uses machine learning based hashing to achieve fast feature aggregation. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach. Keywords Image copy detection Visual words Feature aggregation Machine learning base hashing