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This paper presented an adaptive spatial information fuzzy clustering algorithm to improve the image segmentation effect. The algorithm combined spatial information of image and FCM algorithm, which improved the objective function of FCM. At the same time, it used information maximization to identify noise data and eliminated outliers. Experiment results on compo-site images and MRI brain image database Brainweb show that the presented algorithm can segment image adaptively and identify noise data effectively. The algorithm can also solve the lack of spatial information using FCM to segment images, improve algorithm robustness. The proposed algorithm has better image segmentation effect than several advanced clustering algorithms. [ABSTRACT FROM AUTHOR]

For vehicle to vehicle communication (V2VC) system, due to the high mobility, dynamic network topology and limited network resources, resulting in a communication network congestion problem, this thesis proposed a novel distributed beacon scheduling scheme. It called context-aware beacon scheduling (CABS), which was based on spatial context information similar to TDMA transmission with dynamic scheduling beacon, and transmitted beacon under highly reliable and predictable delays. Based on partial measurement of channel load and context information included in the beacon, each node dynamically scheduled beacon transmission in a distributed manner in the allocated time slot. In the simulation, it used various communication scenarios in the real channel model and IEEE 802.11p PHY/MAC model to evaluate the proposed beacon scheduling scheme. The simulation results show that the performance of CABS in packet transmission rate and channel access delay is better than periodic scheduling. Moreover, CABS scheme meets the needs of security applications. [ABSTRACT FROM AUTHOR]