首页 | 本学科首页   官方微博 | 高级检索  
     

基于朴素贝叶斯分类的路面积雪状态检测
引用本文:孙中华,蒋斌,贾克斌. 基于朴素贝叶斯分类的路面积雪状态检测[J]. 吉林大学学报(工学版), 2013, 0(Z1): 380-383
作者姓名:孙中华  蒋斌  贾克斌
作者单位:北京工业大学电子信息与控制工程学院
基金项目:北京市教委科研计划资助项目(00200054K1006)
摘    要:为解决路面积雪状态(轻微、严重)检测问题以保证行车安全,利用监控视频得到路面实时状态,采用朴素贝叶斯分类方法进行积雪状态检测。首先利用机器视觉和视频目标分割方法提取视频中路面视觉特征,然后采用朴素贝叶斯分类方法进行路面积雪状态分类,通过实验,综合比较了朴素贝叶斯分类与KNN分类、人工神经网络(ANN)、支撑向量机(SVM)在路面积雪状态检测问题中的有效性,结果表明,朴素贝叶斯分类器更适合积雪状态的分类。

关 键 词:路面积雪覆盖  特征信息  朴素贝叶斯分类  视频目标分割

Detection of the road snow coverage status based on naive Bayesian classifier
SUN Zhong-hua,JIANG Bin,JIA Ke-bin. Detection of the road snow coverage status based on naive Bayesian classifier[J]. Journal of Jilin University:Eng and Technol Ed, 2013, 0(Z1): 380-383
Authors:SUN Zhong-hua  JIANG Bin  JIA Ke-bin
Affiliation:(College of Electronic Information and Control Engineering,Beijing University of Technology,Beijing 100124,China)
Abstract:In order to detect the snow coverage status such as mild or heavy coverage on road to keep car running safe,snow coverage detection method together with naive Bayesian classification algorithm was proposed.Firstly,road visual feature was extracted from the video by the method of machine vision and video object segmentation.Then the road snow coverage status was classified with naive Bayesian classifier.The performance of KNN,ANN and SVM classifier for road snow coverage problem were compared.
Keywords:road snow coverage  texture information  naive Bayesian classifier  video object segmentation
本文献已被 CNKI 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号