Tree Root Automatic Recognition in Ground Penetrating Radar Profiles Based on Randomized Hough Transform
Tree Root Automatic Recognition in Ground Penetrating Radar Profiles Based on Randomized Hough Transform
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基于随机Hough变换的探地雷达剖面树根自动识别
DOI：
10.3390/rs8050430
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发表时间：
2016-05-01
期刊：
影响因子：
5
通讯作者：
Cao, Xin
中科院分区：
文献类型：
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作者：
Li, Wentao;Cui, Xihong;Cao, Xin
近年来，探地雷达作为一种无损的地球物理工具，在树根研究中得到了广泛的应用。随着探地雷达数据量的不断增加，开发一种高效的探地雷达树根自动识别系统势在必行。然而，由于根识别问题的复杂性，这方面的研究很少。基于对照和原位GPR实验数据，对随机霍夫变换（RHT）算法在不同中心频率（400 MHz、900 MHz和2000 MHz）下的根目标识别效果进行了评价。在这些数据集中获得了合理的准确率（高识别率和低虚警率），表明将RHT算法应用于树根识别是可行的。此外，我们还评估了根系和土壤因素对识别的影响。研究发现，根间距长度、根方向和土壤杂波噪声对RHT算法的性能影响较大。RHT识别结果可用于地下生态系统根系分布的大规模研究。进一步研究如何降低杂波噪声，提高对复杂根反射的识别能力。
As a nondestructive geophysical tool, Ground penetrating radar (GPR) has been applied in tree root study in recent years. With increasing amounts of GPR data collected for roots, it is imperative to develop an efficient automatic recognition of roots in GPR images. However, few works have been completed on this topic because of the complexity in root recognition problem. Based on GPR datasets from both controlled and in situ experiments, the randomized Hough transform (RHT) algorithm was evaluated in root object recognition for different center frequencies (400 MHz, 900 MHz, and 2000 MHz) in this paper. Reasonable accuracy was obtained (both a high recognition rate and a low false alarm rate) in these datasets, which shows it is feasible to apply the RHT algorithm for root recognition. Furthermore, we evaluated the influence of root and soil factors on the recognition. We found that the performance of RHT algorithm is mainly affected by root interval length, root orientation, and clutter noise of soil. The recognition results by RHT could be applied for large scale root system distribution study in belowground ecology. Further studies should be conducted to reduce clutter noise and improve the recognition of the complex root reflections.