Visual Feature Based Image Forgery Detection


  • D. Vaishnavi
  • D. Mahalakshmi
  • Venkata Siva Rao Alapati





Image splicing forgery, local binary pattern, SVM, BPNN, combined k-NN.


In present days, the images are building up in digital form and which may hold essential information. Such images can be voluntarily forged or manipulated using the image processing tools to abuse it. It is very complicated to notice the forgery by naked eyes. In particular, the copy move forgery is enormously demanding one to expose. Hence, this paper put forwards a method to determine the copy move forgery by extracting the visual feature called speed up robust features (SURF). In the direction to quantitatively analyze the performance, the metrics namely false positive rate and true positive rate are estimated and also comparative study is carried out by previous existing methods.




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