摘要
为提高重叠番茄的识别正确率,提出了一种基于边缘曲率分析的重叠番茄识别方法。该方法从二值图像中提取番茄区域的边缘,并且为进一步计算出边缘点曲率,对边缘点按逆时针方向进行排序。计算出边缘点曲率后,剔除掉曲率异常的边缘点。最后通过对各剩余边缘分别进行圆回归,实现重叠番茄的识别。为减小作业环境光照变化及枝叶遮挡等因素给识别带来的影响,采用了基于归一化色差的固定阈值分割方法,6条边缘识别准则及3条圆回归准则。119幅图像的试验结果表明,存在轻微遮挡的重叠番茄识别正确率为90.9%;遮挡率大于25%且小于50%时,识别正确率为76.9%;遮挡率大于50%时,识别正确率为23%。
In order to improve the recognition accuracy,a method of overlapping tomatoes recognition based on curvature analysis of edge points was presented.Edges of tomatoes were extracted from binary image at first.Then curvature values could be acquired after edge points were sorted counterclockwise.The edge points with abnormal curvature values were abandoned.After circle regression for remaining edges,overlapping tomatoes could be recognized.In order to decrease the negative impact on recognition aroused from environmental lighting variation and occlusion caused by leaves and branches,threshold segmentation method based on normalization aberration,6 rules for edge recognition and 3 rules for circle regression were adopted.The experimental results of 119 images showed that the recognition accuracy for overlapping tomatoes with slight occlusion was 90.9%,it was 76.9% when the occlusion rate was between 25% and 50%,and it was 23% when the occlusion rate was larger than 50%.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2012年第3期157-162,共6页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家高技术研究发展计划(863计划)资助项目(2006AA10Z257)
国家自然科学基金资助项目(61105024)
关键词
采摘机器人
番茄
识别
重叠
曲率
Harvesting robot
Tomato
Recognition
Overlapping
Curvature
