现代电子技术2015，Vol.38Issue(22)：80-83,4.DOI:10.16652/j.issn.1004-373x.2015.22.024
基于K均值聚类算法的雾天识别方法研究
Research on method of foggy weather recognition based on K-means clustering algorithm
摘要
Abstract
To realize the foggy weather automatic recognition with video surveillance equipment,a method of foggy weather automatic recognition based on K-means clustering algorithm is put forward,in which the influence of foggy weather on video image acquisition is analyzed,and the mean value of the image saturability and variance are extracted as the characteristic pa-rameters. The training images are classified by using K-means clustering algorithm to obtain the clustering center of the different image classification. In the test stage,the classification can be completed by calculating the dissimilarity of different images and clustering centers. The experimental results show this method is simple and efficient,and easy to realize large-scale image data processing,and can realize the category labeling after image classification. The recognition accuracy is higher than 90%.关键词
雾天/自动识别/K均值聚类算法/图像饱和度Key words
foggy weather/automatic recognition/K-means clustering algorithm/image saturability分类
信息技术与安全科学引用本文复制引用
孟凡军,李天伟,徐冠雷,韩云东..基于K均值聚类算法的雾天识别方法研究[J].现代电子技术,2015,38(22):80-83,4.基金项目
国家自然科学基金(61250006 （）
61002052 （）
61471412) （）
