基于贝叶斯分类的雾天和雨天两类天气图像自动识别  

Automatic Recognition of Two Different Weathers of Foggy and Rainy Based on Bayesian Classification

作　　者：于浩[1] 王孝通[1] 徐冠雷[1] 

机构地区：[1]海军大连舰艇学院,大连116018

出　　处：《舰船电子工程》2016年第9期73-75,91,共4页Ship Electronic Engineering

基　　金：国家自然科学基金项目(编号:61002052;61471412;61250006)资助

摘　　要：为实现天气现象的自动观测,论文提出了一种基于贝叶斯分类的室外图像的天气现象识别方法,该方法通过提取图像的色相、饱和度和亮度等特征,采用贝叶斯分类,对雨天和雾天两类天气现象进行判断,但所选特征不能对雾天和雨天进行准确判断。To achieve the automatic observation of weather situations, a method based on Bayesion classification to recognize weather situations in outdoor images is presented. It extracted such parameters as hue, saturation and brightness as features to judge the weather situations of foggy and rainy with Bayesian classification But the judgement is not accurate with the selected features.

关 键 词：天气现象识别 图像处理 贝叶斯分类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]