文章基本信息

标题：Road Geometric Features Extraction based on Self-Organizing Map (SOM) Neural Network
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作者：Shu, Zhenyu ; Wang, Dianhong ; Zhou, Cheng 等
期刊名称：Journal of Networks
印刷版ISSN：1796-2056
出版年度：2014
卷号：9
期号：1
页码：190-197
DOI：10.4304/jnw.9.01.190-197
语种：English
出版社：Academy Publisher
摘要：Geometry is the key parameter when extracting road from high-resolution remote sensing imagery. We propose a method for road geometry parameters extraction from high spatial resolution remote sensing imagery automatically based on self-organizing map (SOM) neural network algorithm. SOM is a no-tutor clustering segmentation method and the algorithm is the foundation of later road automatic extraction. Our approach may adjust cluster number and cluster center of the image through analyzing the point density distribution of self-organizing feature map neural network competition layer, which is good for flexible processing on the image excessive segmentation problem and succeed in accurate segmentation object. Then we can extract geometric features of the terrain target. The results are demonstrated that the algorithm proposed is both accurate and effective.
关键词：Organizing Map (SOM) Neural Network;High-Resolution Remote Sensing Imagery;Geometric Features;Road;Geometric Moments