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首页> 外文期刊>WSEAS Transactions on Signal Processing >The Image Analysis Algorithm for the Log Pile Photogrammetry Measurement
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The Image Analysis Algorithm for the Log Pile Photogrammetry Measurement

机译：日志桩摄影测量测量的图像分析算法

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摘要

This paper is devoted to the investigation and development of the algorithm for the log pile photogrammetry measurement on the basis of abuts detection and calculation of their diameters. The algorithm of abuts contours detection and refinement relies on the modified radial symmetry object detection algorithm. The combination of the following methods is implemented at the further stages of the pile measurement algorithm: meanshift clustering, Delaunay triangulation, Boruvka's minimum spanning tree algorithm, watershed and Boykov-Kolmogorov graph cut algorithm. These methods were adapted to the specific of the given task. The testing of the resulting algorithm gives its TPR value at 96,2% which is much higher than other unsupervised training methods. The average error of the algorithm for the log pile photogrammetry measurement in comparison with manual measurement is less than 9.2%. It meets the requirements of the industry standards so the method of the log piles photogrammetry measurement using the developed algorithm can be successfully applied in the activity of forest enterprises.
机译：本文基于邻接检测和直径计算的基础上的日志桩光摄取测量算法的调查和开发。邻接轮廓检测和改进的算法依赖于修改的径向对称对象检测算法。以下方法的组合在桩测量算法的其他阶段实现：意味着群集，Delaunay三角测量，Boruvka的最小生成树算法，流域和Boykov-Kolmogorov Graph Cut算法。这些方法适用于给定任务的特定。结果算法的测试为其TPR值为96,2％，远高于其他无监督的训练方法。与手动测量相比，日志桩摄影测量测量算法的平均误差小于9.2％。它符合行业标准的要求，因此可以在森林企业的活动中成功地应用日志桩光摄影测量的方法。

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