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A robust dynamic programming algorithm to extract skyline in images for navigation

机译:一种强大的动态编程算法,可提取图像中的天际线以进行导航

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摘要

In this paper, a skyline image detection algorithm is proposed for navigation of mobile vehicles or planes in mountainous environments. First, edge detection and subsequent binary thresholding are applied on the luminance component to obtain the edge map, from which a multi-stage graph is constructed for determining the skyline curve by using the dynamic programming (DP) algorithm. In optimal DP search, characteristics (e.g., preferred position and orientation) of the skyline are utilized to help in correct linking of curves. The tolerance in short breakage of skyline curve is considered for robustness consideration. Experiments show that the processing speed is fast (approximately 0.12-0.21 s for a 352 x 240 pixel image on a Pentium-M 1.3 GHz CPU) and promising for real-time applications.
机译:本文提出了一种天际线图像检测算法,用于在山区环境中对移动车辆或飞机进行导航。首先,对亮度分量应用边缘检测和随后的二进制阈值化以获得边缘图,通过使用动态编程(DP)算法从该边缘图构建多级图来确定天际线曲线。在最佳DP搜索中,利用天际线的特征(例如,首选位置和方向)来帮助正确连接曲线。考虑到鲁棒性,考虑了天际线短暂断裂的公差。实验表明,该处理速度较快(奔腾M 1.3 GHz CPU上的352 x 240像素图像约为0.12-0.21 s),并且有望用于实时应用。

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