| 地面雨滴谱观测的图像自动识别方法 |
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| 引用本文： | 安英玉,金凤岭,张云峰,祖雪梅.地面雨滴谱观测的图像自动识别方法[J].应用气象学报,2008,19(2):188-193. |
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| 作者姓名： | 安英玉 金凤岭 张云峰 祖雪梅 |
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| 作者单位： | 1.北京大学物理学院大气科学系, 北京 100871 |
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| 基金项目： | 黑龙江省科技厅科技攻关项目
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黑龙江省气象局重点技术研究项目 |
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| 摘 要： | 该文介绍了地面雨滴谱观测方法的研究, 通过增大取样面积、增加辅助观测手段, 改进了传统的滤纸取样法, 设计出图像自动识别软件应用到雨滴谱资料的处理中, 这种方法不仅可以增加观测的样本数, 以获得稳定的雨滴谱资料, 而且有利于资料的相互配合与分析。对其图像的位置变化、形状改变、滴谱重叠等情况进行验证以及对计算结果进行误差分析, 雨滴谱资料中的单个滴谱图像位置变化和形状变化对图像识别后的结果没有影响, 自动图像处理程序运行结果稳定可靠。程序在处理不粘连的滴谱资料时敏感性较好, 对于大滴溅散而形成的很多溅散滴时, 会处理成很多单独的小雨滴, 同时也说明无法解决溅散问题。在雨滴重叠问题上该程序智能程度不高, 不能真正鉴别是否存在重叠现象, 无法将重叠的雨滴分离开来, 往往会将重叠在一起的雨滴视为一个滴, 从而带来观测雨滴数量减少的现象。从雨滴谱资料处理误差分析上看, 斑迹直径在3~18 mm时相对误差小于6%, 对于直径小于4 mm雨滴误差完全控制在6%以内, 且在处理小滴时误差更小。该方法在地面雨滴谱观测及资料处理中准确度高、性能稳定、实用性强, 为雨滴谱资料的处理分析提供了一个新的思路, 可以应用到实际工作中。
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| 关 键 词： | 地面雨滴谱 图像自动识别 误差分析 |
| 收稿时间： | 2006-11-16 |
| 修稿时间： | 2006年11月16 |
Automatic Identification Methods of Ground Raindrop Spectrum Observation and Image |
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| An Yingyu,Jin Fengling,Zhang Yunfeng,Zu Xuemei.Automatic Identification Methods of Ground Raindrop Spectrum Observation and Image[J].Quarterly Journal of Applied Meteorology,2008,19(2):188-193. |
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| Authors: | An Yingyu Jin Fengling Zhang Yunfeng Zu Xuemei |
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| Affiliation: | 1.Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 1008712.Heilongjiang Provincial Weather Modification Office, Harbin 1500303.Heilongjiang Information Network Center, Harbin 150030 |
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| Abstract: | The ground raindrop spectrum observation method is studied. The traditional filter paper sampling method is improved through enlarging the sample area, and increasing the methods of auxiliary observation. The image automatic identification software is designed and put into application in the processing of the raindrop spectrum data. Not only the sample member to obtain stable raindrop spectra data is enlarged by these ways, but also the mutual coordination and the analysis of the data are benefited. It is tested and result error analysis on its image position variation, the shape change, the drop spectrum overlaps and so on is made.
The pattern recognition results are not influenced by the location and shape changes of single drop image in the data of the raindrop spectra data. The automatic image procedure is stable and reliable. It is very sensible when the separated drop spectra data are dealt with by the procedure. When many scattered drops formed from big drops, a large member of independent small raindrops will be formed, and it manifests that the splash problem can't be solved. The intelligence of the procedure is not high on the problem of raindrop overlapping each other together and it can't be recognized if the phenomenon of overlap really exists, the overlapped raindrops can't be separated and the overlapped drops can't be taken as one drop, so the member of the observing drops is small. From the error analysis of the raindrop spectra data, the relative error of spot mark diameter is smaller than 6% from 3 mm to 18 mm and the error is controlled within 6% for drops smaller than 4 mm, the error is even smaller when handling the small droplets.
The result is obtained that this method is of great accuracy, stable performance, and very practical in the ground raindrop spectrum observation and the data processing. A new thought for the raindrop spectrum data processing analysis is provided and can be applied to the practical work. |
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| Keywords: | the ground raindrop spectrum image automatic iden
tification error analysis |
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