• DocumentCode
    638904
  • Title

    Fogery image splicing detection by abnormal prediction features

  • Author

    Jun Hou ; Haojie Shi ; Yan Cheng ; Ran Li

  • Author_Institution
    Shanghai Key Lab. of Modern Opt. Syst., Univ. of Shanghai for Sci. & Technol., Shanghai, China
  • fYear
    2013
  • fDate
    4-7 Aug. 2013
  • Firstpage
    1394
  • Lastpage
    1398
  • Abstract
    The paper proposes an algorithm to expose photographic manipulation. Splicing photographic merges two or more parts from different photos into one composite. A well-tampered one may not be perceptible by eyes. However, even a good forgery can leave some subtle traces caused by forgery. The proposal algorithm firstly segments photo into several parts under perceptual grouping criterion, minimizing the disassociation between parts and maximizing combination within part with normalized cut algorithm. Then conduct the mean and standard variance features of inharmonic points, as well as 14 Haralick features, then fed them to a support vector machine(SVM) classifier. The test experiments show that the proposal method is effective in exposing large-size splicing photographic.
  • Keywords
    feature extraction; image classification; image reconstruction; image segmentation; support vector machines; Haralick features; SVM; abnormal prediction features; forgery image splicing detection; inharmonic point features; large-size splicing photographic; normalized cut algorithm; perceptual grouping criterion; photo segmentation; photographic manipulation; photographic merge splicing; support vector machine classifier; Feature extraction; Forgery; Image edge detection; Image segmentation; Proposals; Splicing; Support vector machines; Haralick features; SVM classifier; image forgery; normalized cut segmentation; splicing photographic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2013 IEEE International Conference on
  • Conference_Location
    Takamatsu
  • Print_ISBN
    978-1-4673-5557-5
  • Type

    conf

  • DOI
    10.1109/ICMA.2013.6618117
  • Filename
    6618117