Invention Grant
- Patent Title: Image steganalysis based on deep learning
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Application No.: US15557080Application Date: 2015-04-15
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Publication No.: US10223780B2Publication Date: 2019-03-05
- Inventor: Tieniu Tan , Jing Dong , Wei Wang , Yinlong Qian
- Applicant: Institute of Automation Chinese Academy of Sciences
- Applicant Address: CN Beijing
- Assignee: Institute of Automation Chinese Academy of Sciences
- Current Assignee: Institute of Automation Chinese Academy of Sciences
- Current Assignee Address: CN Beijing
- Agency: Howard IP Law, PLLC
- Agent Jeremy Howard
- International Application: PCT/CN2015/076600 WO 20150415
- International Announcement: WO2016/165082 WO 20161020
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06T1/00 ; G06T7/00

Abstract:
The present invention provides a method for detecting image steganography based on deep learning, which comprises: filtering images having steganographic class label or true class label in a training set with a high-pass filter to obtain a training set including steganographic class residual images and true class residual images; training a deep network model on said training set to obtain a trained deep model for steganalysis; filtering the image to be detected with said high-pass filter to obtain a residual image to be detected; detecting said residual image to be detected on said deep model so as to determine whether said residual image to be detected is a steganographic image. The method for detecting image steganography in the present invention can create an automatic blind steganalysis model through feature learning and can identify steganographic images accurately.
Public/Granted literature
- US20180068429A1 Image Steganalysis Based on Deep Learning Public/Granted day:2018-03-08
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