Abstract-NEtwork MObility (NEMO) controls mobility of a number of mobile nodes in a comprehensive way using one or more mobile routers. To choose a route optimization scheme, it is very important to have a quantitative comparison of the available route optimization schemes. The focus of this paper is to analyze the degree of Route Optimization (RO), deploy-ability and type of RO supported by each class in general. The comparison shows the differences among the schemes in terms of issues, such as additional header, signaling and memory requirement. We classify the schemes established on the basic method for route optimization, and equal the schemes based on protocol overhead, such as header overhead, amount of signaling, and memory requirements. Lastly the performance of the classes of different schemes has to be estimated under norms such as available bandwidth, topology of the mobile network and mobility type.
Abstract-Human-lip detection is an important criterion for many automated modern system in present day. Like computerized speech reading, face recognition etc. system can work more precisely if human-lip can detect accurately. There are many processes for detecting human-lip. In this paper an approach is developed so that the region of a human-lip can be detected, we called it lip contour. For this a region-based Active Contour Model (ACM) is introduced with watershed segmentation. In this model we used global energy terms instead of local energy terms because, global energy gives better convergence rate for malicious environment. At the time of ACM initialization by using H∞ based on Lyapunov stability theory, the system gives more accurate and stable result.
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