There are two main alternatives to compress a video. The first one, usually called intraframe approach, pretends to remove the spatial redundancy of an image without destroying important information. These methods are suitable for still image applications such as multimedia, image database, etc. Nevertheless, in applications that use a sequence of image, data such as TV scenes, video conferencing etc, time redundancy can be exploited to increase the compression ratio since consecutive frames are usually highly correlated. This second group of methods is called interframe approach, and pretends to remove temporal redundancy. In the second approach, motion estimation of sequence frames must be computed. In the proposed work, the interframe approach is implemented. In the field of motion estimation for video compression many techniques have been applied. Block-based motion estimation approaches are the most common procedures applied using various algorithms. The full search algorithm (FSA) provides the best performance but at very expensive computational cost. To reduce this computational requirement, fast search algorithms have been developed, among them being the conventional three-step algorithm (TSA). In the proposed work OTS, and TSS methods of ME are implemented in addition to a new developed Hybrid Method (HM). The interframe approach select a number of frames that will compress using compression system that is different than ME techniques, these frames are called Anchor frames (AF). In the proposed work there are two models that developed for video coding, the first one develop a compression system that depend on FDCT transform that a new derivation of DCT, where this transform is speed up through a new derivation that fully documented in the proposed work, and the second model develop the Fractal coding as compression system for AF. The disadvantage of Fractal coding is the expensive time that Fractal needs to complete its search. This problem is solved in the proposed work through fasting Fractal Search using distributed system that divide the Fractal search on the total number of Servers that shared on the network. The proposed work is implemented using Visual Basic 6.0 as a programming language. The fidelity measure MSE and PSNR are used to check the result of the whole developed techniques.