Extracting vein of leaf image based on K-means clustering

被引：0
|
作者：
机构：
[1] School of Physic and Telecommunication Engineering, South China Normal University
来源：
Li, F. (ganguli@126.com) | 1600年 / Chinese Society of Agricultural Engineering卷 / 28期
关键词：
Clustering algorithms; HSI color space; Image processing; Image segmentation; Vein extraction;
D O I：
10.3969/j.issn.1002-6819.2012.17.023
中图分类号：
学科分类号：
摘要：
Leaf is the primary part of a plant and the major site of food production for the plant. Leaf vein extraction and analysis are useful for investigation of leaf and plant structures. In this paper, a vein extraction algorithm based on the K-means clustering is proposed. Using intensity information, K-means clustering is carried out. According to the clustering results, the boundary of the leaf is extracted and leaf images are divided into two types, the uniform illumination leaf image and the nonuniform illumination leaf image. For a uniform illumination leaf image, vein is directly extracted based on the clustering results. However, for the nonuniform illumination leaf image, some mesophylls are removed first, and K-means clustering is then used to extract the vein. The results show that the proposed algorithm can greatly reduce the misclassification error rate.
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页码：157 / 162
页数：5
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