Real-time, large-scale duplicate image detection method based on multi-feature fusion

被引：0
作者：
Ming Chen
Yuhua Li
Zhifeng Zhang
Ching-Hsien Hsu
Shangguang Wang
机构：
[1] Zhengzheng University of Light Industry,Software Engineering College
[2] Foshan University,School of Mathematics and Big Data
[3] Chung Hua University,Department of Computer Science and Information Engineering
[4] Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology
来源：
Journal of Real-Time Image Processing | 2017年 / 13卷
关键词：
Duplicate image detection; Multi-feature fusion; Image retrieval;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Recently, using old or irrelevant images in microblogs to spread false rumors has become increasingly rampant. Therefore, tracking and verifying the sources of images has become essential. In order to solve this problem, this paper provides a real-time, large-scale duplicate image detection method based on multi-feature fusion. This method firstly uses multi-feature fusion to improve retrieval accuracy. Then, by Hbase optimization, it uses a bloom filter and range query to improve retrieval efficiency. Experimental results show that, compared with existing algorithms, this method has higher precision and recall rates. Meanwhile, real-time responsiveness and scalability of the approach also meet real-world needs.
引用
收藏
页码：557 / 570
页数：13
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