The objective of this paper is generation of an algorithm that will separate moving foreground from a stationary background in a general video sequence. We use the different models to calculate the foreground motion in a robust estimation framework. Segmentation of objects in image sequence is very important in many aspects of multimedia applications. We describe a system for representing moving images from the multi-layered sequence. This work realizes a motion- based image isolation algorithms for isolating the moving image in a multi-layered moving image sequence. The system has been proposed here which can efficiently segment a moving foreground object from a given image sequence with still background. The modules of the system are developed using MATLAB and verified for its functionality. In our system different algorithms like LMSE, Block-matching algorithm, motion tracing and recursive algorithms are used to estimate foreground image segmentation for Multi-layered video sequence. Experimental results are given to show the efficiency of our methods.

Social Network is an emerging E-service for content sharing sites (CSS). It is emerging service which provides a reliable communication, through this communication a new attack ground for data hackers; they can easily misuses the data through these media. Some users over CSS affects users privacy on their personal contents, where some users keep on sending unwanted comments and messages by taking advantage of the users’ inherent trust in their relationship network. By this privacy of the user data may be loss for this issue this paper handles the most prevalent issues and threats targeting different CSS recently. This proposes a privacy policy prediction and access restrictions along with blocking scheme for social sites using data mining techniques. To perform this, the system utilizes APP (Access Policy Prediction) and Access control mechanism by applying BIC algorithm (Bayesian Information Criterion).