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当前位置: 首页 > 文章 > 基于视觉识别的小麦收获作业线快速获取方法 农业机械学报 2016,47 (11) 32-37
Position: Home > Articles > Fast Edge Detection Method for Wheat Field Based on Visual Recognition Transactions of the Chinese Society for Agricultural Machinery 2016,47 (11) 32-37

基于视觉识别的小麦收获作业线快速获取方法

作  者：
赵腾;野口伸;杨亮亮;石井一畅;陈军
单  位：
西北农林科技大学机械与电子工程学院;北海道大学农学院车辆机器人实验室
关键词：
小麦;收获;视觉识别;导航线;激光作业线识别系统;互相关函数法
摘  要：
针对小麦生长分布不均等情况下激光作业线检测系统精度偏低的问题,提出了基于视觉的小麦收获作业线快速获取的方法。通过对成熟期麦田的彩色图像进行对比度增强和降低亮度的处理,将其转换为灰度图像,利用阈值分割方法分离已收获与待收获区域,对二值图像采用互相关函数法检测已收获与待收获区域的分界点,利用Hough变换法拟合目标直线。所提方法在激光作业线识别系统的基础上扩大了视野范围,并限制了图像处理的范围,试验结果表明该方法对小麦收获作业线的检测结果平均偏差为2.35 cm,标准差为3.26,能够满足小麦收获导航线识别的要求,是一种有效的检测算法。
译  名：
Fast Edge Detection Method for Wheat Field Based on Visual Recognition
作  者：
Zhao Teng;Noboru Noguchi;Yang Liangliang;Kazunobu Ishii;Chen Jun;College of Mechanical and Electronic Engineering,Northwest A&F University;Vehicle Robotics Laboratory,Graduate School of Agriculture,Hokkaido University;
关键词：
wheat;;harvesting;;visual recognition;;navigation line;;crop edge detection system based on laser rangefinder;;cross correlation function method
摘  要：
To overcome the shortages of the developed method for edge detection system based on laser rangefinder( LF),a vision based fast edge information acquiring algorithm for the LF system was proposed. Inverse perspective mapping( IPM) geometrical transform was used to remove the perspective effect on original mature wheat field. The image after IPM transformation was then processed by illumination reduction and contrast enhancement to make the difference between cut and uncut wheat field more evidently,and then transferred into grayscale image. Threshold segmentation method based on histogram was used to convert grayscale image into a binary image,so as to distinguish the cut and uncut wheat. The target points were clustered by adopting cross correlation method on each horizontal scan line in the binary image,and then Hough transform was used to detect the edge line between cut and uncut wheat. The proposed method extended the field of view of the edge detection system based on LF,and owing to the LF system the region of interest area for image processing was well restricted. The results showed an average deviation of 2. 35 cm,with standard deviation of 3. 26. This edge detector providing satisfied performance under different conditions,was an effective edge detection method,and met the demand of recognition for navigation path in wheat harvesting.

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