Seam Carve Detection Using Convolutional Neural Networks

Mehtab Iqbal, Lei Chen, Hengfeng Fu, Yun Lin

Research output: Contribution to book or proceedingConference articlepeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationAdvanced Hybrid Information Processing - 2nd EAI International Conference, ADHIP 2018, Proceedings
EditorsShuai Liu, Gelan Yang
PublisherSpringer Verlag
Pages392-407
Number of pages16
ISBN (Print)9783030190859
DOIs
StatePublished - 2019
Event2nd EAI International Conference on Advanced Hybrid Information processing, ADHIP 2018 - Yiyang, China
Duration: Oct 5 2018Oct 6 2018

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume279
ISSN (Print)1867-8211

Conference

Conference2nd EAI International Conference on Advanced Hybrid Information processing, ADHIP 2018
Country/TerritoryChina
CityYiyang
Period10/5/1810/6/18

Keywords

  • Convolutional Neural Networks
  • Seam carving
  • Steganalysis

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