Diploid genetic algorithms (DGAs) promise robustness as against simple genetic algorithms which only work towards optimization. Moreover, these algorithms outperform others in dynamic environments. The work examines the theoretical aspect of the concept by examining the existing literature. The present work takes the example of dynamic TSP to compare greedy approach, genetic algorithms and DGAs. The work also implements a greedy genetic approach for the problem. In the experiments carried out, the three variants of dominance were implemented and 115 runs proved the point that none of them outperforms the other.
In digital era, it has become easy to modify any image. Due to this the trust and validation of it is going to lose. Now it has become major problem of digital world to regain the lost trust. The background behind the modification and any changes in an image is easy availability of software tools on internet. Images can be transformed from one image format to another and any part of image can be altered pixel by pixel. Before the digital age, it was literally easy to detect the altered photographs. But now with the advent in the commercial software like various image photo editing software like Adobe Photoshop, XnView; ProShow Gold etc. make image forgery simple, the tampering of the photographs have become very easy, can be carried out without any noticeable signs of tampering and it is becoming harder to expose and mark the authentic ones. With the increased dependency over the digital images for exchanging the information, the need to keep their authenticity increases and digital images also use as authenticated facts for an offence. If it will not contain the authenticity then a problem will arise. An image forgery is made either by summing some templates, or hiding some kind of information in an image, in which the consistency is lost. This paper identifies the key methods for detecting forgery in the digital images. To identify and detect the forged areas, the image is divided into overlapped patches of some fixed size. In our paper we will discuss the correlation method, that how it find outs the forged part in an image. Firstly, the digital image tampering process is discussed. After that, it shows that different algorithms have different approaches to detect the forgery.
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