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当前位置: 首页 > 文章 > 基于达芬奇平台的联合收获机视觉导航系统路径识别 农业机械学报 2012,43 (1) 271-276
Position: Home > Articles > Visual Navigation System Path Recognition Algorithm Based on DaVinci Platform for Combine Harvester Transactions of the Chinese Society for Agricultural Machinery 2012,43 (1) 271-276

基于达芬奇平台的联合收获机视觉导航系统路径识别

作  者：
张成涛;谭彧;吴刚;王书茂
单  位：
中国农业大学工学院
关键词：
联合收获机;视觉导航;路径识别;达芬奇平台;图像纹理
摘  要：
针对联合收获机视觉导航对实时性及鲁棒性要求,采用了基于达芬奇平台的路径识别算法实现方案。在分析小麦收获视频图像纹理度量的基础上,提出了基于改进平滑度纹理特征的视觉导航路径识别算法。该算法利用水平方向上图像平滑度纹理特征,把原亮度图像转换成水平方向平滑度图像,然后采用自适应阈值分割图像的边界点,最后通过Hough变换确定视觉导航的路径。为验证该算法在达芬奇平台的运行效果,对联合收获机田间收获小麦进行导航实验。结果表明:算法运行实时性高,识别路径平均速度可达28.6帧/s;算法鲁棒性好,对多种环境下的路径识别有较好的适应性;算法运行稳定可靠,持续运行时间无限制。
译  名：
Visual Navigation System Path Recognition Algorithm Based on DaVinci Platform for Combine Harvester
作  者：
Zhang Chengtao1,2 Tan Yu1 Wu Gang1 Wang Shumao1(1.College of Engineering,China Agricultural University,Beijing 100083,China 2.Automobile Engineering Department,Guangxi University of Technology,Liuzhou 545006,China)
关键词：
Combine harvester,Visual navigation,Path recognition,DaVinci platform,Image texture
摘  要：
According to combine visual navigation of real-time and robustness requirement,based on the DaVinci platform,a path recognition algorithm was designed.After analyzing the texture measure in the image of wheat harvest,the path recognition algorithm of visual navigation,on account of an improved smoothness texture feature,was put forward.The original brightness image was converted into horizontal smoothness image,by the image texture feature of the horizontal smoothness.The harvest boundary was extracted from the smoothness image by using adaptive threshold segmentation,and finally visual navigation path could be determined by Hough transform.In order to validate the algorithm in the operation of the DaVinci platform,the navigation experiments of wheat harvest by combine harvester were conducted.The experimental results showed that the algorithm had the high real-time and good robustness.Its average rate of recognizing navigation line was up to 28.6 frame per second.Path recognition effect was good in a variety of environments.Algorithm operation was stable and reliable,and to continue operating time was unlimited.

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