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Automated Plant Species Identification Using Leaf Shape-Based Classification Techniques: A Case Study on Iranian Maples
Iranian Journal of Science and Technology, Transactions of Electrical Engineering ( IF 2.4 ) Pub Date : 2021-01-05 , DOI: 10.1007/s40998-020-00398-2
Mojgansadat Mohtashamian , Mahmood Karimian , Faisal Moola , Kaveh Kavousi , Ali Masoudi-Nejad

Foliar characteristics, especially the overall leaf shape, are useful features for the taxonomic identification of plants. Computer-aided plant species identification systems make it possible to investigate a large number of leaves in a short period of time. In this study, a fully automatic system was developed to accurately classify eight species of maples ( Acer L.) in Iran using the leaf shape characteristics of harvested leaves. Maples show a broad range of leaf morphology, and the provided dataset is a diverse collection of simple leaves which can be a good representative of woody plant leaves with any overall shape and margin pattern. The applied method consisted of preprocessing, feature extraction and classification steps. A new method for petiole removal and a new feature as teeth indicator are presented in preprocessing and feature extraction parts, respectively. Using support vector machine (SVM) classifier, experimental results showed a high accuracy of 98.60% ± 1.20 for the identification of maple species. Focusing on extracting robust features, the proposed method offers considerable potential to speed up expert identification of maples with high accuracy whose output can be applied to computational botany, conservation planning and natural resource management.

中文翻译:

使用基于叶形的分类技术自动识别植物物种:伊朗枫树案例研究

叶特征,尤其是整体叶形,是植物分类鉴定的有用特征。计算机辅助植物物种识别系统可以在短时间内调查大量叶子。在这项研究中,开发了一个全自动系统,使用收获叶子的叶形特征对伊朗的八种枫树 (Acer L.) 进行准确分类。枫树表现出广泛的叶子形态,提供的数据集是简单叶子的多样化集合,可以很好地代表具有任何整体形状和边缘图案的木本植物叶子。应用的方法包括预处理、特征提取和分类步骤。在预处理和特征提取部分分别提出了一种去除叶柄的新方法和一种作为牙齿指示器的新特征。使用支持向量机(SVM)分类器,实验结果表明枫树物种识别的准确率为98.60%±1.20。所提出的方法专注于提取鲁棒特征,提供了相当大的潜力,可以以高精度加快枫树的专家识别,其输出可应用于计算植物学、保护规划和自然资源管理。
更新日期:2021-01-05
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