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Recognizing matured cinnamon tree using image processing techniques

机译:使用图像处理技术识别成熟的肉桂树

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Cinnamon cultivation is the main income source of a set of areas in Sri Lanka. Peeling cinnamon is a complex task of the cinnamon harvesting process after identifying the matured cinnamon trees. Expertise knowledge is essential to identify matured trees using the traditional method. Otherwise, it may cause the wastage of cinnamon, by cutting immature cinnamon trees. This research addresses the automated system to recognize the matured cinnamon trees using image processing techniques which can be used to identify the matured cinnamon trees without any expert knowledge. All the trees that are selected to this study are more than three year old. Image preprocessing, algorithm selection and use the Speeded Up Robust Features (SURF) features to extract data from leaves and at last, prediction of the maturity level of cinnamon trees using Support Vector Machine (SVM) classifier are the main phases of this study. Hundred cinnamon trees were tested from two different farms and the system performed 68.0% accuracy for matured trees and 86.0% accuracy for immature trees.
机译:肉桂种植是斯里兰卡一系列地区的主要收入来源。识别成熟的肉桂树后,剥皮肉桂是肉桂收获过程中的一项复杂任务。专业知识对于使用传统方法识别成熟树木至关重要。否则,可能会由于砍伐未成熟的肉桂树而导致肉桂浪费。这项研究针对使用图像处理技术来识别成熟肉桂树的自动化系统,该技术可用于在没有任何专业知识的情况下识别成熟肉桂树。本研究选择的所有树木均已使用三年以上。图像预处理,算法选择以及使用加速鲁棒特征(SURF)特征从叶片中提取数据,最后,使用支持向量机(SVM)分类器预测肉桂树的成熟度是本研究的主要阶段。对来自两个不同农场的一百棵肉桂树进行了测试,该系统对成熟树木的准确度为68.0%,对于未成熟树木的准确度为86.0%。

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