Airport Detection Base on Support Vector Machine from A Single Image

Yanyun Qu, Cuihua Li, N. Zheng
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引用次数: 39

Abstract

Airport is one of the key transportation targets. Airport detection is very important in military and civil fields. A novel method to detect airports from a single image is proposed in this paper. It combines texture features with shape features, and uses support vector machine as a classification function. Canny edge detector is firstly used, then short lines and curves are removed, and long straight lines are detected by Hough transform, at last the airport runways are discriminated by support vector machine. The experimental results demonstrate the efficacy of the proposed automatic airport-detection method
基于支持向量机的单幅图像机场检测
机场是交通运输的主要目标之一。机场探测在军事和民用领域都具有十分重要的意义。提出了一种从单幅图像中检测机场的新方法。它将纹理特征与形状特征相结合,并使用支持向量机作为分类函数。首先使用Canny边缘检测器,然后去除短的直线和曲线,利用Hough变换检测长直线,最后利用支持向量机识别机场跑道。实验结果证明了该方法的有效性
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