Detection of seam carving in JPEG images

Wen Lung Chang, Timothy K. Shih, Hui Huang Hsu

Research output: Contribution to conferencePaperpeer-review

16 Scopus citations

Abstract

The content-aware image retargeting algorithm is used for modifying the image size into the suitable size in different device. Seam carving is a kind of content aware image retargeting algorithm. In this paper, based on the blocking artifact characteristics matrix (BACM), we propose a method to detect seam carving in natural images without knowledge of the original image. In detail, for the original JPEG images, the BACM exhibits regular symmetrical shapes; for the images that are damaged, the regular symmetrical property of the BACM is destroyed. After found BACM from images, we define 18 features to detect the damage from BACM to train a support vector machine (SVM) classifier for recognizing whether an image is an original or it has been modified by seam-carving. We show that BACM is useful for detect the damage by seam-carving in JPEG format images.

Original languageEnglish
Pages632-637
Number of pages6
DOIs
StatePublished - 2013
Event2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013 - Aizuwakamatsu, Japan
Duration: 2 Nov 20134 Nov 2013

Conference

Conference2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013
Country/TerritoryJapan
CityAizuwakamatsu
Period2/11/134/11/13

Keywords

  • Image forensics
  • Seam carving
  • Seam insertion
  • Steganalysis features
  • Tamper detection

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