An Efficient Approach for Identification of Copy- Move Image Forgery using SURF and SIFT based Techniques

Internet has changed the world of computers and how we use them. Now there is no field left that may not require internet. It has impacted mostly the fields like image processing, machine learning, cyber security, data mining etc. Technological developments today have made the life so comfortable and easy but also put forward a challenge of authentication of digital data generated from various domains. This has become a major concern for security. To address this concern, we are encapsulating facet point juxtaposition, adaptive over dissection for forgery identification in our proposal. We have based our work on Key point and Section based forgery identification techniques. Adaptive non-intersecting, irregular sections are utilized to uncover suspicious sections in the images. Dissection algorithms are used to assist in this process. Facet points are mined by comparing and juxtaposition each section with its facets. Super pixels are used instead of facet points in the proposed forgery section mining system. The neighbouring sections are melded into facet sections to acquire merged sections which have similar color facets. To end the process morphological operations are used over merged sections to obtain forgery section. The outcomes obtained shows that this proposed algorithm can achieve superior and accurate outcomes even in most critical constraints when compared to other existing approaches.