• DocumentCode
    3547389
  • Title

    Detection of seam carving in JPEG images

  • Author

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

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Jhongli, Taiwan
  • fYear
    2013
  • fDate
    2-4 Nov. 2013
  • Firstpage
    632
  • Lastpage
    638
  • 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.
  • Keywords
    feature extraction; image forensics; image processing; support vector machines; JPEG images; SVM classifier; blocking artifact characteristics matrix; content aware image retargeting algorithm; image size; natural images; regular symmetrical shapes; seam carving detection; support vector machine; Accuracy; Cloning; Feature extraction; Image coding; Support vector machines; Training; Transform coding; Image forensics; Seam carving; Seam insertion; Steganalysis features; Tamper detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Awareness Science and Technology and Ubi-Media Computing (iCAST-UMEDIA), 2013 International Joint Conference on
  • Conference_Location
    Aizuwakamatsu
  • Type

    conf

  • DOI
    10.1109/ICAwST.2013.6765516
  • Filename
    6765516