Seam Carve Detection Using Convolutional Neural Networks

Mehtab Iqbal; Lei Chen; Hengfeng Fu; Yun Lin

Advanced Hybrid Information Processing. Second EAI International Conference, ADHIP 2018, Yiyang, China, October 5-6, 2018, Proceedings

Research Article

Seam Carve Detection Using Convolutional Neural Networks

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@INPROCEEDINGS{10.1007/978-3-030-19086-6_44,
    author={Mehtab Iqbal and Lei Chen and Hengfeng Fu and Yun Lin},
    title={Seam Carve Detection Using Convolutional Neural Networks},
    proceedings={Advanced Hybrid Information Processing. Second EAI International Conference, ADHIP 2018, Yiyang, China, October 5-6, 2018, Proceedings},
    proceedings_a={ADHIP},
    year={2019},
    month={5},
    keywords={Steganalysis Seam carving Convolutional Neural Networks},
    doi={10.1007/978-3-030-19086-6_44}
}

Mehtab Iqbal
Lei Chen
Hengfeng Fu
Yun Lin
Year: 2019
Seam Carve Detection Using Convolutional Neural Networks
ADHIP
Springer
DOI: 10.1007/978-3-030-19086-6_44

Mehtab Iqbal¹, Lei Chen¹^,*, Hengfeng Fu², Yun Lin²

1: Georgia Southern University
2: Harbin Engineering University

*Contact email: lchen@georgiasouthern.edu

Abstract

Seam carving is a form of content-aware image modification. This modification can vary from resizing to clipping of content within an image. This can be easily used to alter images to achieve steganographic goals or the propagation of misleading information. Deep learning, particularly Convolutional Neural Networks have become prolific in today’s image-based intelligent systems. However, it has been found that convolutional networks specialized for image classification tend to perform poorly for steganalysis—specifically seam carving. In this paper, we propose a convolutional neural network architecture which is able to learn the nuances of seam carved images.

Keywords: Steganalysis Seam carving Convolutional Neural Networks

Published: 2019-05-13
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-030-19086-6_44