• DocumentCode
    1582208
  • Title

    Image forgery detection using SVM classifier

  • Author

    Reshma, P.D. ; Arunvinodh, C.

  • Author_Institution
    MTECH Comput. Sci. & Eng., R. Coll. Of Eng. & Technol., Akkikavu, India
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Unlike text, images represent an effective communication media for humans. Today we use photographs for variety of applications. Traditionally, everyone have confidence in the content of the image. Sometimes, a picture printed in a newspaper is accepted as a certification of the truthfulness of the news. As the technology develops, we can´t trust images. Image manipulation can be done easily by using photo editing tools. As a result, we have to prove the originality of images. One of the most common forms of image modification is the image composition. Composite image is created from two or more image sources. All the different images are taken from the different devices and at different world view conditions. Digital forensics field has emerged to help restore some trust to digital images. When creating a composite image, it becomes hard to match the color of one object with reference to the other. This paper describes a technique for detecting digital image forgery using illuminant color.
  • Keywords
    copy protection; image classification; image colour analysis; image forensics; image matching; image restoration; support vector machines; Image manipulation; SVM classifier; digital forensic field; digital image forgery technique; illuminant color; image composition; image restoration; object color match; photo editing tool; Conferences; Face; Feature extraction; Forgery; Image color analysis; Light sources; Lighting; Composite image; Digital forensics; Illuminant color;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4799-6817-6
  • Type

    conf

  • DOI
    10.1109/ICIIECS.2015.7193202
  • Filename
    7193202