Matlab Project with Source Code Image Forgery Detection || Final Year Project || IEEE Based Project

ABSTRACT

             Image forgery means manipulation of digital image to conceal meaningful information of the image. The detection of forged image  is  driven  by  the  need  of  authenticity  and  to  maintain integrity of the image. A copy move forgery detection theme victimization adaptive  over  segmentation  and have  purpose feature matching is proposed. The proposed scheme integrates both block based   and   key point based   forgery   detection  methods. The proposed adaptive over segmentation algorithm segments  the  host  image  into  non over lapping  and  irregular blocks adaptively. Then, the feature points are extracted from  each  block  as  block  features,  and  the  block  features  are matched with one another to locate the labeled feature points; this   procedure can   approximately indicate   the   suspected forgery    regions.    To    detect    the    forgery regions more accurately, we propose the forgery region extraction algorithm which  replaces  the  features  point  with  small super  pixels  as feature  blocks  and  them  merges  the  neighboring  blocks  that have  similar  local color  features  into  the  feature  block  to generate    the    merged    regions. Finally,    it    applies    the morphological  operation  to  merged  regions  to  generate  the detected forgery regions. In cut paste image forgery detection, proposed   digital   image   forensic techniques capable   of detecting  global  and  local contrast  enhancement,  identifying the use of histogram equalization.

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Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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