基于颜色和纹理特征的航空图像异常检测

Fabian Zavala-Vazquez, F. E. Correa-Tome, Uriel H. Hernandez-Belmonte, J. Ramirez-Paredes
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引用次数: 1

摘要

数字图像中异常区域的检测可用于许多应用,如安全、搜索和救援行动、危险识别和工业检查。在这项工作中,我们提出了一种基于颜色和纹理特征的异常检测方法,应用于非线性一类分类器,并表明它提供了很好的结果,即使与两类分类器相比也是如此。我们的方法是轻量级的,旨在在无人驾驶飞行器的机载计算机上实现。
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Anomaly Detection in Aerial Imagery Using Color and Texture Features
The detection of anomalous regions in digital images can be used in many applications, such as security, search and rescue operations, hazard identification and industrial inspection. In this work, we present an anomaly detection method based on color and texture features applied to a non-linear one-class classifier, and show that it provides excellent results, even when compared to a two-class classifier. Our approach is lightweight and aimed at its implementation on an onboard computer for an Unmanned Aerial Vehicle.
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