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

Bor-Horng Sheu, Fu-Shan Chou, Chien-Kuei Chang, Yuan-Shien Zhen, Wen-Chih Lin, Wen-Ping Chen
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引用次数: 1

Abstract

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.
基于台湾樟科和壳斗科植物叶片轮廓的物种鉴别研究
本文利用台湾樟科和壳斗科植物叶片形态的多种形态特征,结合模糊理论和模板匹配技术,开发了一个叶片物种识别平台。首先,通过图像预处理,对叶片长度和宽度进行归一化采样,提取叶片二值轮廓,然后分别提取叶片形态凸壳、质心-轮廓距离和锯齿形分割等特殊几何特征;最后,利用模糊理论进行样本特征训练和模板比对,判断叶片的物种识别。本研究以54种樟科和壳斗科混合植物为研究对象,利用著名的k-NN算法和本文提出的方法分析了叶片识别的效果。
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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