Over the last few years a new field of technology i.e. Vehicular Ad-hoc Networks (VANET) has been generated through Wireless Sensor Networks (WSN) and it attracts very large number of researchers. Now VANET has become a very interesting and developing area in the WSN, because it provides traffic and road safety by connecting vehicles travelling on the road. Also it provides communication between moving vehicles to the other vehicles. In VANET, data is transferred from one vehicle to another, so the security is a major issue, because any successful attack in VANET can cause large destruction. Routing between the moving vehicles is very challenging and quite interesting. This paper includes the Position Based Routing (PBR) protocol to provide the connection between moving vehicles on the road for the purpose of safety, communication and also for the driver's comfort. In this we are evaluating the GPSR (Greedy Perimeter Stateless Routing) which is very popular Position Based Routing in VANET. In order to evaluate the realistic simulation environment for vehicles we are using NS2 (Network Simulator 2) and SUMO (Simulation for Urban Mobility). The performance is measured in the form of some parameters like Network throughput, Packet delivery ratio (PDR), NRL (Network Routing Load) and Average end to end delay.
The process of Face Recognition comprises of Face Detection, feature extraction and verification or identification. The extraction and identification are stages in the FR process. Many face recognition algorithms have been developed. This has resulted in development of manifold robust techniques such as background removal, illumination normalization and others which support the algorithm to withstand the undesirable effects and improve the success rate. This paper provides a survey and method for face pose estimation. This method is based on feature extraction points of two different face poses and then matched points between these two face poses will give the results. This method is one of the simplest methods for low resolution images.
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