This paper proposes a distributed dynamic k-medoid clustering algorithm for wireless sensor networks (WSNs),DDKCAWSN.Different from node-clustering algorithms and protocols for WSNs,the algorithm focuses on clustering data in the network.By sending the sink clustered data instead of practical ones,the algorithm can greatly reduce the size and the time of data communication,and further save the energy of the nodes in the network and prolong the system lifetime.Moreover,the algorithm improves the accuracy of the clustered data dynamically by updating the clusters periodically such as each day.Simulation results demonstrate the effectiveness of our approach for different metrics.
将Tony F Chan提出的基于曲线进化、Mumford-shah泛函和level set技术的没有边界泛函的活动轮廓模型与Gabor滤波器相结合,利用Tony F Chan提出的不依赖于边界梯度的活动轮廓能够检测出边界梯度较弱的物体边界与Gabor滤波器能在不同方向和频率增强图像的特点,先对原始细胞图像进行不同角度、不同频率Gabor滤波从而在不同方向增强细胞边界削弱细胞内部信息,然后把不同方向滤波后的图像融合以得到边界增强噪声减少的图像,最后在该图像上应用活动轮廓取得了较好的分割效果。
Improving the precision of calibration is always the hotspot in the field of intelligent robot.A Hand-Eye cali...
Gao Yang,Wang Haixia,Xie Peng,Cao Maoyong Key Laboratory for Robot&Intelligent Technology of Shandong province,Shandong University of Science and Technology,Qingdao 266510,P.R.China
