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基于边缘曲率分析的重叠番茄识别
引用本文:项荣,应义斌,蒋焕煜,饶秀勤,彭永石.基于边缘曲率分析的重叠番茄识别[J].农业机械学报,2012,43(3):157-162.
作者姓名:项荣  应义斌  蒋焕煜  饶秀勤  彭永石
作者单位:1. 浙江大学生物系统工程与食品科学学院,杭州310058;中国计量学院质量与安全工程学院,杭州310018
2. 浙江大学生物系统工程与食品科学学院,杭州,310058
基金项目: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)
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%。

关 键 词:采摘机器人  番茄  识别  重叠  曲率

Recognition of Overlapping Tomatoes Based on Edge Curvature Analysis
Xiang Rong,Ying Yibin,Jiang Huanyu,Rao Xiuqin and Peng Yongshi.Recognition of Overlapping Tomatoes Based on Edge Curvature Analysis[J].Transactions of the Chinese Society of Agricultural Machinery,2012,43(3):157-162.
Authors:Xiang Rong  Ying Yibin  Jiang Huanyu  Rao Xiuqin and Peng Yongshi
Institution:Zhejiang University;China Jiliang University;Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University
Abstract: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%.
Keywords:Harvesting robot  Tomato  Recognition  Overlapping  Curvature
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