Optimization techniques play a major role in real-world problems, As many cases in which decisions are made are based on random research. But choosing the optimization technology is a big challenge for the user. The cuckoo search algorithm is one of the modern optimization techniques that can replace many of the traditional techniques used, The cuckoo bird use a Levi's flight strategy based on the egg laying method to extract a solution to the problem. The presented work will provide a review of the original cuckoo search algorithm with mentioning some types of developed and hybrid cuckoo search algorithm as well as some of their applications.

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In this search, two methods were used to include the watermark in the video. The first method was based on DCT (Discrete Cosine Transform), the second method was based on an algorithm SVD (Singular Value Decomposition) for the purpose of converting video to frequency domain. The process of embedding the watermark in both methods was done after the original video was divided into a set of frames, and one frame was divided into a block of 8 x 8 and the DCT on each block when using the first method and the SVD algorithm when using the second method. And then include the Bit Binary for the watermark inside the center of the cluster. Random selection of video frames and rows of watermark images has been adopted in both ways. The performance of the two methods was assessed using the experimental tests PSNR, MSE and NC.The experimental results show that both methods have achieved a good understanding and high resistance against various attacks, adopted Matlab 2013a language.

Efficiency an d retrieval time are very important issues in any content-based image retrieval system. In this study, an efficient image retrieval system was introduced depending on several features extracted from the database images, namely color moment (Mean, Standard Deviation), GLCM, and DWT(only LL-sub band). To increase the retrieval speed, Cuckoo search algorithm was used to select the important positions that contain full power features from the (LL-sub band). On using the Cuckoo search algorithm, only (50) important positions were chosen out of the total (24576) positions within (LL-sub band). These positions were stored for later use when entering a query image. Thus, the time taken to retrieve images was greatly reduced and this process also increased the efficiency of the system due to the fact that the selected positions gave the lowest distance measures between the query images and the similar images when evaluated using Manhattan distance measure. Two effectual performance measures (precision & recall) were used to calculate the accuracy of the system. The findings proved the system efficiency when compared to other previous works.