Abstract
Image forgery is one of the well known fields in which researches continuously exploring new areas. In digital image forgery one can change image in many ways using several software’s, researchers exploring new algorithms to detect image forgery areas and change it to original pixel values if possible. In this paper we employed ACO (Ant Colony Optimization) to find areas which are manipulated with some software. The experimental results prove that ACO is better than existing methods of detecting tampered regions in digital photo images.
Highlights
Active based approach requires extra operations and harms the original image so passive based approach is better than the active based
Xin Wang et al [3] put forward a passive blind digital image forgery detection based on consistency of defocus blur
Image patches which are at similar distance from lens have similar blur kernels and this consistency of blur is broken in the forged images which are used to detect the digital image forgery
Summary
Active based approach requires extra operations and harms the original image so passive based approach is better than the active based. In our work we are using passive based approach and this is the most preferred approach to detect the digital image forgery for the past recent years. The rest of the paper is organized as follows.
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