Department of Electrical Engineering, University of Washington, Seattle, WA 98195, USA.
IEEE Trans Image Process. 2011 Dec;20(12):3534-43. doi: 10.1109/TIP.2011.2155079. Epub 2011 Jun 7.
Power-line-strike accident is a major safety threat for low-flying aircrafts such as helicopters, thus an automatic warning system to power lines is highly desirable. In this paper we propose an algorithm for detecting power lines from radar videos from an active millimeter-wave sensor. Hough Transform is employed to detect candidate lines. The major challenge is that the radar videos are very noisy due to ground return. The noise points could fall on the same line which results in signal peaks after Hough Transform similar to the actual cable lines. To differentiate the cable lines from the noise lines, we train a Support Vector Machine to perform the classification. We exploit the Bragg pattern, which is due to the diffraction of electromagnetic wave on the periodic surface of power lines. We propose a set of features to represent the Bragg pattern for the classifier. We also propose a slice-processing algorithm which supports parallel processing, and improves the detection of cables in a cluttered background. Lastly, an adaptive algorithm is proposed to integrate the detection results from individual frames into a reliable video detection decision, in which temporal correlation of the cable pattern across frames is used to make the detection more robust. Extensive experiments with real-world data validated the effectiveness of our cable detection algorithm.
架空线路碰撞事故对直升机等低空飞行的飞行器构成了重大的安全威胁，因此，需要一种自动的架空线路警示系统。本文提出了一种利用主动毫米波传感器的雷达视频来检测架空线路的算法。霍夫变换用于检测候选线路。主要的挑战是由于地面回波，雷达视频非常嘈杂。噪声点可能落在同一条线上，这导致霍夫变换后的信号峰值与实际电缆线相似。为了将电缆线与噪声线区分开来，我们训练了一个支持向量机来进行分类。我们利用了由于电磁波在电力线周期性表面上的衍射而产生的布喇格模式。我们提出了一组用于分类器的特征来表示布喇格模式。我们还提出了一种切片处理算法，支持并行处理，并改善了在杂乱背景下对电缆的检测。最后，提出了一种自适应算法，将来自各个帧的检测结果集成到可靠的视频检测决策中，该算法利用了帧间电缆模式的时间相关性来提高检测的鲁棒性。通过真实数据的广泛实验验证了我们的电缆检测算法的有效性。
