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A Study on Species Identification Based on Leaf Contours of Taiwan Lauraceae and Fagaceae Plants

机译:基于台湾月桂科和菊科植物叶片轮廓的物种鉴定研究

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In this paper, a leaf species identification platform for Taiwan Lauraceae and Fagaceae plants is developed by using a variety of morphological features of leaf shape in combination with fuzzy theory and template matching technology. Firstly, the binary leaf contour is extracted by normalized sampling of leaf length and width through image preprocessing, and then the special geometric features of leaves, such as morphological convex hull, centroid-contour distance and serrated shape segmentation, are extracted respectively. Finally, the sample feature trainings and template comparison are carried out by fuzzy theory to judge the species identification of leaves. In this study, 54 species of mixed Lauraceae and Fagaceae were used to analyze the effect of leaf identification by the well-known algorithm k-NN and a method proposed in this paper.
机译:本文结合模糊理论和模板匹配技术,利用多种叶片形态特征,开发了台湾月桂科和菊科植物的叶种鉴定平台。首先通过图像预处理对叶长和宽进行归一化采样,提取二元叶轮廓,然后分别提取叶片的特殊几何特征,如形态凸包,质心轮廓距离和锯齿形状分割。最后,通过模糊理论对样本进行特征训练和模板比较,以判断叶片的物种识别。在这项研究中,使用54种月桂科和菊科科植物的混合物,通过众所周知的算法k-NN和本文提出的方法来分析叶片识别的效果。

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