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Development of GUI For Automated Oil Palm Tree Counting Based On Remote Sensing Imagery

机译:基于遥感影像的油棕树自动计数GUI的开发

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This paper presents a novel non-destructive approach for individual oil palm tree counting using remote sensing imagery. This study has three main objectives which are to identify the best techniques for tree counting based on SVM model, to assess tree counting techniques for oil palm and to develop graphic user interface (GUI) for oil palm tree counting based on oil palm tree recognition techniques. Ten subset images with size of 400 x 400 pixels were used and each dataset are arranged categorically according to type of oil palm, which are matured and young. Three algorithm are used in this study, which are Gray-Level Co-occurrence Matrix (GLCM), Haar and Biorthogonal wavelet and template matching. All three algorithms are tested by using Support Vector Machine (SVM) to see which algorithms gives highest accuracy and will be used for automated oil palm tree counting. Graphical User Interface (GUI) also created for user to use the function in future. Software used in this study is MATLAB and all process of tree counting are carried out in this software.
机译:本文提出了一种新颖的非破坏性方法,可利用遥感图像对单个油棕树进行计数。这项研究的三个主要目标是确定基于SVM模型的最佳树木计数技术,评估油棕的树木计数技术以及开发基于油棕树识别技术的油棕树计数图形用户界面(GUI) 。使用十个大小为400 x 400像素的子集图像,并且根据油棕的类型对每个数据集进行分类排列,这些油棕既成熟又年轻。本研究使用了三种算法:灰度共生矩阵(GLCM),Haar和双正交小波以及模板匹配。通过使用支持向量机(SVM)对这三种算法进行了测试,以查看哪种算法具有最高的准确性,并将用于自动油棕榈树计数。还创建了图形用户界面(GUI),供用户将来使用该功能。本研究中使用的软件是MATLAB,并且树计数的所有过程都在该软件中执行。

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