基于吊蔓绳的温室番茄主茎秆视觉识别(英文)  

Vision-based detection of tomato main stem in greenhouse with red rope

作　　者：王新忠[1,2] 韩旭[1,2] 毛罕平[1,2] 

机构地区：[1]江苏大学现代农业装备与技术教育部重点实验室,镇江212013 [2]江苏省农业装备与智能化高技术研究重点实验室,镇江212013

出　　处：《农业工程学报》2012年第21期135-141,F0004,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：Science and Technology Pillar Program of Jiangsu Province (BE2011346);Agricultural Machinery Tri-projects of Jiangsu Province (NJ2011-46);National Natural Science Foundation of China (No.60575020);Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No.09KJD210003);Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions

摘　　要：为了精确识别番茄植株以供精确对靶喷施,该文提出一种基于温室吊蔓绳对番茄主茎进行检测识别的算法。通过分析番茄作物图像在HSI颜色空间的分布特性,基于H分量应用Otsu分割算法对番茄作物图像进行二值化处理,以突出图像中吊蔓绳区域。利用细化算法提取出吊蔓绳区域离散特征点簇,并采用最小二乘法直线拟合特征点簇获取吊蔓绳位置。试验结果表明,处理分辨率640×480像素的图像平均用时0.16s,对100张图像进行识别试验,正确率达93%,该算法提取吊蔓绳和番茄主茎间的最大距离偏差为48像素单位,能够准确识别番茄主茎秆,具备较强的鲁棒性。In order to identify tomato plants for target spraying, an algorithm was presented to detect main stem of tomato relative to the rope which was used to fix main stem. The distribution characteristics of tomato images due to HSI color space were analyzed, and the images were then binarized using Otsu segmentation method based on H histogram and the rope region was extracted. The rope line was fit with least square method based on the set of discrete points extracted by thinning methodologies. Experiment results indicated that the average processing time for each image of 640×480 pixels was 0.16 s, the recognition accuracy of 100 images was 93%, and the maximum deviation between the rope and tomato main stem was 48 pixels. The algorithm can detect the main stem accurately with strong robust.

关 键 词：机器视觉 图象分割 最小二乘法 主茎秆 番茄 MATLAB 

分 类 号：S126[农业科学—农业基础科学]