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A hybrid model for seam-carving and JPEG compression operation chain detection
BIN Muyu,YANG Gaobo *,DONG Xiaoxu
Department of Information Science and Engineering, Hunan University,Changsha 410082
*Correspondence author
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Funding: National Natural Science Foundation of China（No.61572183, 61379143）, National Key R&D Program of China（No.2018YFB1003205）
Opened online:29 April 2019
Accepted by: none
Citation: BIN Muyu,YANG Gaobo,DONG Xiaoxu.A hybrid model for seam-carving and JPEG compression operation chain detection[OL]. [29 April 2019] http://en.paper.edu.cn/en_releasepaper/content/4748494
 
 
Seam carving, which is known as content-aware image resizing, leaves no visible traces in resized images. Though several approaches have been presented for seam carving forgery detection, there are few works about the operation chain detection of both seam carving and JPEG compression. In this paper, a hybrid model is proposed to distinguish JPEG-Seam carving-JPEG images from single and double compression JPEG images. Both spatial-domain and transform-domain features are extracted for operation chain detection. Experiment results show that the proposed approach can efficiently detect seam carving operation.
Keywords:information processing technology; seam carving; operation chain; JPEG compression; difference matrix
 
 
 

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