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An Intelligence Monitoring System for Abnormal Water Surface Based on ART

机译:基于ART的水面异常智能监测系统

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摘要

Classing object is an important step for the high-level visions processing tasks, such as security managing, and abnormality event analysis. In this paper, we address these challenges of abnormal water surface monitoring in real-world unconstrained environments where the background is complex and dynamic. In the algorithm proposed, we extract the moment features of water surface in a color space, and a technique is developed to monitor the abnormal surface of water based on ART. Experimental results show that our algorithm works efficiently and robustly.
机译:分类对象是高级视觉处理任务(例如安全性管理和异常事件分析)的重要步骤。在本文中,我们解决了在背景复杂且动态的现实世界中不受约束的环境中异常水面监测的挑战。在提出的算法中,我们提取了颜色空间中水面的矩特征,并开发了一种基于ART的水面异常监测技术。实验结果表明,该算法有效,鲁棒地工作。

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