基于ART的异常水面智能监测系统

Youfu Wu, Jianjun Zhuo, Jing Wu
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引用次数: 2

摘要

对象分类是安全管理、异常事件分析等高级视觉处理任务的重要步骤。在本文中,我们解决了这些挑战的异常水面监测在现实世界中,背景是复杂和动态的无约束环境。该算法在颜色空间中提取水面的矩特征,并开发了一种基于ART的水面异常监测技术。实验结果表明,该算法具有良好的鲁棒性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Intelligence Monitoring System for Abnormal Water Surface Based on ART
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.
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