山东农业大学学报（自然科学版）2016，Vol.47Issue(2)：259-263,5.DOI:10.3969/j.issn.1000-2324.2016.02.019
多特征融合与相关向量机的火灾烟雾识别方法
A Method of Identification for the Smog in the Fire Based on Multi-feature Fusion and Relevance Vector Machine
摘要
Abstract
Aiming at a defect in identification for the fire smog described by a single feature and a simple combination in order to improve the accuracy of identification for the fire smog, this paper put forward a new method which fire smog was identified by the Multi-feature fusion and Relevance Vector Machine(MF-RVM). Firstly, the static and dynamic features were obtained in a suspected fire smog area and then combined them with principal component analysis to eliminate the redundancy message between features. Lastly, relevance vector machine was used to train the fusion features and established an identification model for a fire smog to carried out the simulation test on the Matlab 2012 platform. The results showed that the proposed method could effectively identify a fire smog to be more than 95% an average recognition accuracy and increase the efficiency of identification so as to satisfy the real time requirements of identification for fire smog.关键词
火灾烟雾/运动特征/相关向量机Key words
Fire smog/motion features/relevance vector machine分类
信息技术与安全科学引用本文复制引用
蔡荣文..多特征融合与相关向量机的火灾烟雾识别方法[J].山东农业大学学报（自然科学版）,2016,47(2):259-263,5.基金项目
浙江省高等学校访问学者教师专业发展项目:基于图像处理的火灾烟雾智能探测研究(FX2014196) （FX2014196）
