Recognizing Image Imitation Using Knowledge Based Classifier For Copy-Move Forgery Detection

Rakhi S. Pagar S. Pagar

Abstract


In todays digital world, Digital images have a very
significant role in various fields. Due to the abundantly available
imaging technologies it becomes easy to modify images, which
afterward becomes difficult to use digital images in applications
like medical imaging, digital forensics, journalism, scientific
publications, etc. where their authenticity is judge. One of the
mostly found types of image imitation is Copy-Move forgery
and Creation of Contrast Enhancement. This paper proposed
Copy Move Forgery and Global Contrast Enhancement Detection
method for detecting the Image Forgery and copied region within
the forged image. The proposed technique is robust against
compressed images of all image formats. The technique is more
efficiently able to detect small, medium as well as large size region
of a forged image with the metadata extraction. Index Terms

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