NDLI: Two-stream neural networks to detect manipulation of JPEG compressed images

Content Provider	IET Digital Library
Author	Kim, H. G. Park, J. S. Kim, D. G. Lee, H. K.
Abstract	With the rapid spread of image editing software, anyone can easily create, distribute, and forge images. Although techniques to detect image forgery have been widely studied, current techniques have significant limitations, such as specific file formats, manipulations, or compression qualities. Although deep learning techniques have been introduced to detect various manipulations, such as blurring, median filtering, and Gaussian noise, these techniques are only suitable to detect forgeries of uncompressed images, and are difficult to apply in practice because most images are compressed for distribution. Therefore, a two-stream neural network approach for image forensics that is robust to compression is proposed. The two-stream neural network is based on constrained convolutional neural network and Markov characteristics to consider compression. Experimental results show that the proposed method overcomes current technique limitations.
Starting Page	354
Ending Page	355
Page Count	2
ISSN	00135194
Volume Number	54
e-ISSN	1350911X
Issue Number	Issue 6, Mar (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/54/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2017.4444
Journal	Electronics Letters
Publisher Date	2018-02-13
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Compression Qualities Computer Vision And Image Processing Technique Constrained Convolutional Neural Network Current Technique Current Technique Limitations Data Compression Deep Learning Technique Forgeries Gaussian Noise Image Coding Image Editing Software Image Forensics Image Forgery Learning in AI Manipulations Median Filtering Neural Computing Technique Neural Nets Optical, Image And Video Signal Processing Rapid Spread Significant Limitations Specific File Formats Stream Neural Network Two-stream Neural Network Approach Uncompressed Image
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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