Anomaly Detection in Aerial Imagery Using Color and Texture Features

被引：1
|
作者：
Zavala-Vazquez, Fabian [1 ]
Correa-Tome, Fernando E. [1 ]
Hernandez-Belmonte, Uriel H. [2 ]
Ramirez-Paredes, Juan-Pablo [1 ]
机构：
[1] Univ Guanajuato, Dept Elect Engn, Irapuato Salamanca Campus, El Copal, Mexico
[2] Univ Guanajuato, Dept Art & Enterprise, Irapuato Salamanca Campus, El Copal, Mexico
来源：
2019 INTERNATIONAL CONFERENCE ON MECHATRONICS, ELECTRONICS AND AUTOMOTIVE ENGINEERING (ICMEAE 2019) | 2019年
关键词：
SCALE;
D O I：
10.1109/ICMEAE.2019.00016
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：45 / 49
页数：5
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