| 变光照环境下农用车辆导航方法 |
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| 引用本文： | 赵 博,范云涛,毛文华,周 鹏,张小超.变光照环境下农用车辆导航方法[J].农业工程学报,2012,28(26):193-196. |
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| 作者姓名： | 赵 博 范云涛 毛文华 周 鹏 张小超 |
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| 作者单位： | 土壤植物机器系统技术国家重点实验室，中国农业机械化科学研究院，北京 100083;土壤植物机器系统技术国家重点实验室，中国农业机械化科学研究院，北京 100084;土壤植物机器系统技术国家重点实验室，中国农业机械化科学研究院，北京 100085;土壤植物机器系统技术国家重点实验室，中国农业机械化科学研究院，北京 100086;土壤植物机器系统技术国家重点实验室，中国农业机械化科学研究院，北京 100087 |
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| 基金项目： | ational Natural Science Foundation (No.31101086), National High Technology Research and Development Program of China (No. 2012AA10A503) and National Basic Research Program of China (No. 2010CB735707). |
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| 摘 要： | 摘要：为了使农业车辆视觉导航系统对不同的光照环境具有良好的适应性，分析了不同光照环境对农业车辆导航路径的影响。在普通环境导航路径识别方法的基础上，针对影响较大的强光照环境，提出一种基于直方图均衡与中心线检测的适应于不同光照环境的导航路径识别方法。大量田间试验证明，该方法的识别准确率为92%，平均消耗时间为245m，能够快速、可靠、准确的提取导航路径特征。该研究可为农业车辆视觉航系统的研发提供参考。
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| 关 键 词： | 机器视觉，导航，路径识别，变光照环境，农业车辆 |
| 收稿时间： | 2012/5/14 0:00:00 |
| 修稿时间： | 9/5/2012 12:00:00 AM |
Path recognition method of agricultural vehicle in different illumination environments |
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| Zhao Bo,Fan Yuntao,Mao Wenhu,Zhou Peng and Zhang Xiaochao.Path recognition method of agricultural vehicle in different illumination environments[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(26):193-196. |
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| Authors: | Zhao Bo Fan Yuntao Mao Wenhu Zhou Peng and Zhang Xiaochao |
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| Abstract: | In order to improve the adaptability of the vision navigation system in the agricultural vehicle to various environments, the path recognition method for different illumination environments was proposed in this paper. Firstly, the influence of different illumination environments on the path recognition for the vision navigation system of the agricultural vehicle was investigated. Secondly, on basis of path recognition in the ordinary environment, a new method mainly composed of histogram equalization algorithm and center line detecting algorithm was applied in the path recognition in different illumination environment. Finally, the many images of different illumination environment were used to verify proposed method. Experimental results showed that the new method was effective in various illumination environments, and could obtain the target navigation path reliably and accurately. The recognition correct rate of the vision navigation system was 92%, and the average cost time was 245 ms. The research can provide a reference for design of the vision navigation system in the agricultural vehicle. |
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| Keywords: | computer vision navigation path recognition various environments agricultural vehicle |
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