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The Detection of Naval Vessels by Fusion of Edge and Color Background Models

机译:边缘和彩色背景模型融合的海军血管检测

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The detection of naval vessels in open water is a difficult challenge, with many applications from harbor monitoring to proximity security systems for ocean-faring ships. Background modelling is an effective method of detecting candidate targets, and we describe a framework that improves the operational robustness by the interaction of two different Mixture of Gaussian (MoG) models. These results are then processed by a tracking system that accurately detects moving vessels. The algorithm performs well in varying environmental conditions with good real-time performance characteristics.
机译:在露天水中的海军血管检测是一个艰难的挑战,许多来自港口监测的许多应用,对海洋船舶的近距离安全系统。 背景技术建模是一种检测候选目标的有效方法,我们描述了一种通过两个不同的高斯(MOG)模型的两种不同混合物的相互作用来改善操作鲁棒性的框架。 然后通过准确地检测移动容器的跟踪系统处理这些结果。 该算法在不同的环境条件下表现良好,具有良好的实时性能特征。

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