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Edge Detection for Hardwood Seedlings Leaves Based on Intuitionistic Fuzzy Set

机译:基于直觉模糊集的硬木苗木叶片边缘检测

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The task of reliably segmenting leaves is significant for plants recognition and reconstruction. Leaves image segmentation, registration and identification are based on edge detection. In this paper, a novel method to detect hardwood leaves edges is proposed, which clusters, thresholds, and then detects edges of hardwood seedlings leaves using intuitionistic fuzzy set (IFS) theory. Clustering segments image into several clusters and histogram threshold eliminates unwanted clusters that are not related to leaves region. Finally, image edge is detected, where a clear boundary is obtained. Proposed method performs better than classical edge detection methods. Experiments for kinds of hardwood seedlings are carried out and the results indicate that the proposed method is effectiveness to detect the leaves edges.
机译:可靠地分割叶片的任务对于植物的识别和重建非常重要。叶片图像的分割,配准和识别基于边缘检测。本文提出了一种基于直觉模糊集理论的硬木叶片边缘聚类,阈值检测硬木幼苗叶片边缘的新方法。聚类将图像分为几个聚类,直方图阈值可消除与叶区域无关的不需要的聚类。最后,检测图像边缘,获得清晰的边界。提出的方法比传统的边缘检测方法表现更好。进行了各种硬木幼苗的实验,结果表明该方法是检测叶片边缘的有效方法。

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