2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
Login Paper Search My Schedule Paper Index Help

My ICASSP 2021 Schedule

Note: Your custom schedule will not be saved unless you create a new account or login to an existing account.
  1. Create a login based on your email (takes less than one minute)
  2. Perform 'Paper Search'
  3. Select papers that you desire to save in your personalized schedule
  4. Click on 'My Schedule' to see the current list of selected papers
  5. Click on 'Printable Version' to create a separate window suitable for printing (the header and menu will appear, but will not actually print)

Paper Detail

Paper IDIFS-1.3
Paper Title A FEATURES DECOUPLING METHOD FOR MULTIPLE MANIPULATIONS IDENTIFICATION IN IMAGE OPERATION CHAINS
Authors Jiaxin Chen, Xin Liao, Hunan University, China; Wei Wang, Institute of Automation, Chinese Academy of Sciences, China; Zheng Qin, Hunan University, China
SessionIFS-1: Multimedia Forensics 1
LocationGather.Town
Session Time:Tuesday, 08 June, 13:00 - 13:45
Presentation Time:Tuesday, 08 June, 13:00 - 13:45
Presentation Poster
Topic Information Forensics and Security: [MMF] Multimedia Forensics
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Recently, many forensic techniques have been developed to detect the use of a certain processing operation. When utilizing several manipulations to alter an image, artifacts left by manipulations that have been applied later can potentially disguise traces left by manipulations that were applied earlier. Therefore, the detection of manipulations become difficult. In this paper, we focus on identifying the manipulations in an image operation chain composed of multiple manipulations in a certain order. To address this issue, we analyze the relationship between manipulations identification and blind signal separation. Then, we propose a features decoupling method based on blind signal separation, which decouples the coupled features due to the superimposed processing artifacts and exploits the decoupled features to identify multiple operations. The experiments carried out on two image operation chains confirm the effectiveness of the proposed method.