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Maximizing Network Capacity through a Novel Topology Control Scheme
SHWETHA.O, PRAMOD KUMAR.P Student, CSE, SR Engineering College, Warangal, India Assistant Professor, IT, SR Engineering College, Warangal, India
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Abstract: This paper presents a survey on different algorithms for road extraction from high resolution satellite images behaviour of roads in Ribbon Snakes, Genetic Algorithm, Extended Kalman Filtering based on edge extraction. It has only few parameters to be adjusted. The Support Vector Machine is used to trained extraction of urban and sub urban areas. The Genetic Algorithm allows for a bridging of shadows and partially occluded areas using heavily disturbed evidence in the image. The road network represents the curve segment to be extracted from the image using a curve linear structure detector, which are accurately detected by curve segment. Extended Kalman Filter combined with a special Particle Filter, the EKF traces to a road until a stopping criterion is met. Then instead of terminating process, they have been continued with the process.
Keywords: Ribbon Snakes, Genetic Algorithm, Extended Kalman Filtering (EKF), Particle Filtering (PF), Synthetic Aperture Radar (SAR), Road Detection, Remote Sensing.
Keywords: Ribbon Snakes, Genetic Algorithm, Extended Kalman Filtering (EKF), Particle Filtering (PF), Synthetic Aperture Radar (SAR), Road Detection, Remote Sensing.
How to Cite:
[1] SHWETHA.O, PRAMOD KUMAR.P Student, CSE, SR Engineering College, Warangal, India Assistant Professor, IT, SR Engineering College, Warangal, India, βMaximizing Network Capacity through a Novel Topology Control Scheme,β International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)
