基于图像处理技术的火灾识别方法的应用与研究Application and research on fire disaster identification method based on image processing technology
袁斌
摘要(Abstract)：
针对火灾图像特征提取方法使用的特征单一造成火灾误报率高的问题,在最小二乘支持向量机超参数选取在快速留一法的基础上,结合共轭梯度算法,提出改进的最小二乘支持向量机的火灾图像处理方法,构建了FR-LSSVM模型。通过对比采用BP神经网络、最小二乘法支持向量机、FR-LSSVM和标准支持向量机的实验结果可以得出,改进算法具有更好的稳定性、更快的运算速度和更高的识别率,有利于提高火灾识别的有效性,进而保护人们的生命财产安全。
关键词(KeyWords)： 图像处理;火灾识别;快速留一法;共轭梯度;BP神经网络;最小二乘支持向量机
基金项目(Foundation):
作者(Author): 袁斌
DOI: 10.16652/j.issn.1004-373x.2018.13.010
参考文献(References)：
- [1]王瑜,苑津莎,尚海昆,等.组合核支持向量机在放电模式识别中的优化策略[J].电工技术学报,2015,30(2):229-236.WANG Yu,YUAN Jinsha,SHANG Haikun,et al.Optimization strategy research on combined-kernel support vector machine for partial discharge pattern recognition[J].Transactions of China electrotechnical society,2015,30(2):229-236.
- [2]孙茜,封皓,曾周末.基于图像处理的光纤预警系统模式识别[J].光学精密工程,2015,23(2):334-341.SUN Qian,FENG Hao,ZENG Zhoumo.Recognition of optical fiber pre-warning system based on image processing[J].Optics and precision engineering,2015,23(2):334-341.
- [3]潘海洋,杨宇,郑近德,等.基于径向基函数的变量预测模型模式识别方法[J].航空动力学报,2017,32(2):500-506.PAN Haiyang,YANG Yu,ZHENG Jinde,et al.Variable predictive model based RBF class discriminate method[J].Journal of aerospace power,2017,32(2):500-506.
- [4]朱思思,丁德红,陈朝迎,等.基于图像处理的森林火灾识别方法研究[J].红外技术,2016,38(5):440-446.ZHU Sisi,DING Dehong,CHEN Chaoying,et al.The research of forest fire recognition method based on image processing[J].Infrared technology,2016,38(5):440-446.
- [5]王媛彬.基于图像特征的煤矿火灾检测与识别研究[D].西安:西安科技大学,2013.WANG Yuanbin.Research on fire detection and recognition in coal mine based on image features[D].Xi’an:Xi’an University of Science and Technology,2013.
- [6]潘庆先,董红斌,韩启龙,等.一种基于BP神经网络的属性重要性计算方法[J].中国科学技术大学学报,2017,47(1):18-25.PAN Qingxian,DONG Hongbin,HAN Qilong,et al.A computing method for attribute importance based on BP neural network[J].Journal of University of Science and Technology of China,2017,47(1):18-25.
- [7]石祥滨,阳柯,张德园.基于对称神经网络的图像分类[J].小型微型计算机系统,2017,38(3):578-583.SHI Xiangbin,YANG Ke,ZHANG Deyuan.Symmetric deep neural network for image classification[J].Journal of Chinese computer systems,2017,38(3):578-583.
- [8]赵望达,李卫高,熊涵予,等.一种新型BP神经网络模型在火灾探测信息处理中的应用[J].铁道科学与工程学报,2015,12(5):1212-1218.ZHAO Wangda,LI Weigao,XIONG Hanyu,et al.Improved neural network model application in fire detection[J].Journal of railway science and engineering,2015,12(5):1212-1218.
- [9]何晨阳,周孟然,闫鹏程,等.图像处理与BP神经网络在矿井火灾隐患识别中的应用[J].桂林理工大学学报,2016,36(3):615-618.HE Chenyang,ZHOU Mengran,YAN Pengcheng,et al.Application of image processing and BP neural network on mine fire potential hazard identification[J].Journal of Guilin University of Technology,2016,36(3):615-618.
- [10]沈艳,瞿传柱,张琦智.改进最小二乘支持向量机算法及其在故障诊断中的应用[J].计算机应用,2016,36(z2):93-95.SHEN Yan,QU Chuanzhu,ZHANG Qizhi.Improved least squares support vector machine algorithm and its application in fault diagnosis[J].Journal of computer applications,2016,36(S2):93-95.
- [11]FENG Y,JIA B,YAN G,et al.Prediction model of highspeed oblique cutting temperature based on LS-SVM[J].International journal of advanced manufacturing technology,2016,85(1):317-324.