Image segmentation model of plant lesion based on genetic algorithm and fuzzy neural network

被引：0
|
作者：
Guan H. [1 ]
Xu S. [2 ]
Tan F. [1 ]
机构：
[1] College of Information Technology, Heilongjiang Bayi Agricultural University
[2] School of Computer and Information Technology, Northeast Petroleum University
来源：
Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery | 2010年 / 41卷 / 11期
关键词：
Fuzzy neural network; Genetic algorithm; Plant disease; Plant lesion image;
D O I：
10.3969/j.issn.1000-1298.2010.11.032
中图分类号：
学科分类号：
摘要：
Aiming at the ambiguity and uncertainty of lesion field image border, using inference rule of fuzzy logic and self-adaptive of neural network, the self-adaptive and fuzzy neural network model was proposed to be the decision system for extracting the diseased spots, and the initial values of adjusting parameters were optimized by using genetic algorithm which enhanced the speed of network training, overcame the local minimum of traditional gradient descent method. The experimental result showed that model had many advantages including accuracy, convergence, stability, robustness, and was easy to implement when implied in extracting the diseased spots of potato early blight.
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收藏
页码：163 / 167
页数：4
相关论文
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