Automatic Detection of the Main Vine and Branches of Tomato Plants Grown in Greenhouses

A. M. E. Mesalami, Soad F. Ibrahim, M. Moussa
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Abstract

An algorithm for real-time detection of plants main vine and branches using the Distance Regularized Level Set Evolution (DRLSE) algorithm is presented in this paper. The algorithm tracks the target plant in the foreground from a set of seeding points automatically located on the main vine. The location of the seeding pints is determined in two different ways using the Hough transform and template searching. Test images are captured inside a greenhouse and include a huge amount of clutter from adjacent plants. The clutter creates a complex environment for traditional segmentation techniques to detect branches of the plant in the foreground. Images are normalized to speed the execution time of the DRLSE and protect the algorithm from local minima traps. Results demonstrate the capability of the algorithm in detecting the main vine and major branches. This algorithm is good for real-time maintenance (i.e., deleafing) using robots inside greenhouses.
温室栽培番茄植株主藤和分枝的自动检测
提出了一种基于距离正则化水平集进化(DRLSE)算法的植物主藤和枝的实时检测算法。该算法通过自动定位在主藤上的一组播种点来跟踪前景中的目标植物。采用霍夫变换和模板搜索两种不同的方法确定种子点的位置。测试图像是在温室内拍摄的,其中包括来自相邻植物的大量杂波。杂波为传统的分割技术在前景中检测植物的分支创造了一个复杂的环境。图像被归一化,以加快DRLSE的执行时间,并保护算法免受局部最小陷阱的影响。结果表明,该算法具有较好的主枝和主枝检测能力。该算法适用于在温室内使用机器人进行实时维护(即删除)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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