无线传感器网络中并行多径路由径间干扰已成为多径路由提高网络传输带宽的障碍,目前主要通过采用异步方式建立多条路径的方法达到最小化并行多径路由干扰的目的。由于没有考虑路径建立之间的关联关系,这些方法利用多次广播建路径,造成巨大网络开销。本文充分挖掘路径建立之间的关联关系,利用已建路径上各节点到目的节点的跳数信息在网络中构造梯度信息,提出基于梯度值的MR2-GRADE(Maximally Radio-disjoint Multipath Routing based on GRADE)路由算法建立后续路径,避免多次广播,降低网络开销。模拟结果表明:MR2-GRADE比采用广播方式建后续路径的MR2路由开销低,更适合节点稠密情况下的传感器网络。
We propose a novel method for curve structure extraction of cartoon images. Our method handles two types of cartoon curves, decorative curves and boundary curves, in a uniform way. The method consists of two steps. Fi...
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We propose a novel method for curve structure extraction of cartoon images. Our method handles two types of cartoon curves, decorative curves and boundary curves, in a uniform way. The method consists of two steps. First, we calculate curve points by applying non-maximal suppress on secondary derivative of cartoon images. Second, these curve points are linked together to form structure curves while unreliable curves are removed away. Compared to curve structure extraction algorithm proposed by Steger, the number of curves generated by our algorithm is only 19% of Steger’s on average, with better curve quality. Furthermore, more accurate curve position can be obtained by our method.
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