摘要
正确将垄行分割为"垄"和"沟"是单目视觉导航农业机械在垄间自主耕种的关键。虽然垄行的颜色、纹理随土壤和开沟方式的不同呈现出多样性,但垄行在图像中的尺度由近及远逐渐变小。基于垄行尺度上的这一特征,提出了垄行多尺度分割算法。该方法利用高斯差分金字塔结构构建垄行多尺度特征集,再根据不同尺度下垄行特征的分布情况,对多尺度特征集中的图像进行中心化、灰度值饱和化处理;最后,将每一张特征图像分段并分别进行加权求和运算得到垄沟特征图像从而将图像分割为"垄区"和"沟区"。利用40个垄行样本对本文算法进行分割实验,结果表明,所提算法能有效分割出不同尺度中的垄行,而且能有效抑制土壤的局部特征所产生的噪声。
The ability to correctly divide the ridges into"ridges"and"grooves"is the key to the independent cultivation of agricultural machinery in the ridges.Although the color and texture of the ridge row show diversity depending on the soil and the way of trenching,the scale of the ridge row in the image gradually decreases from near to far.Based on this feature on the ridge scale,this paper proposes a multi-scale segmentation algorithm for ridge row.The method uses the Gaussian difference pyramid structure to construct the multi-scale feature set of ridge rows.Then,according to the distribution of ridge rows in different scales,the image in multi-scale feature set is centralized and saturated with gray value.Finally,each feature image is segmented and weighted respectively to divide the image into"ridge area"and"ditch area".Experiments on 40 ridge rows show that the proposed algorithm can effectively segment ridge rows in different scales,and effectively suppress the noise generated by local soil characteristics.
作者
陈颉颢
蒋红海
Chen Jiehao;Jiang Honghai(Department of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming,Yunnan 650500,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2020年第8期153-160,共8页
Laser & Optoelectronics Progress
关键词
图像处理
视觉导航
多尺度分割
高斯差分金字塔
垄行
image processing
vision navigation
multi-scale segmentation
Gaussian difference pyramid
ridge row
作者简介
蒋红海,E-mail:836078614@qq.com。
