Security is an important issue in communication and storage of images, and encryption is one the ways to ensure security. Image encryption has applications in internet communication, multimedia systems, medical imaging, telemedicine, and military communication. However, Images are different from text. Although we may use the traditional cryptosystems (such as RSA and DES) to encrypt images directly, it is not a good idea for two reasons. One is that the image size is almost always greater than that of text. Therefore, traditional cryptosystems need much time to encrypt the image data. The other problem is that the decrypted text must be equal to the original text. Due to the characteristic of human perception, a decrypted image containing small distortion is usually acceptable. The main idea behind the present work is that an image can be viewed as an arrangement of bits, pixels and blocks. Image retrieval methods based on color, texture, shape and semantic image are discussed, analyzed and compared. The semantic-based image retrieval is a better way to solve the “semantic gap” problem, so the semantic-based image retrieval method is stressed in this paper. Other related techniques such as relevance feedback and performance evaluation also discussed. In the end of paper the problems and challenges are proposed. In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. Many of these collections are the product of digitizing existing collections of analogue photographs, diagrams, drawings, paintings, and prints. Usually, the only way of searching these collections was by keyword indexing, or simply by browsing. Digital images databases however, open the way to content-based searching. In this paper we survey some technical aspects of current content-based image retrieval systems. Problem statement: The main object of implementing this paper is to retrieve the video sequence by using the frame which is specified by the user. To overcome the private key, here we use the public key to generate the encryption and the decryption process. Even though this process, is useful to retrieve the whole video sequence by using the any other frame obtained. Here the retrieval process is done by using the SIFT feature which is taken from the image. The SIFT feature is more efficient to grasp the features from the image. So that the required Data / Features are taken by the SIFT feature.