计算机应用与软件Issue(4)：153-155,180,4.DOI:10.3969/j.issn.1000-386x.2015.04.037
Adaboost算法在图像型火灾探测中的应用研究
ON APPLYING ADABOOST ALGORITHM IN IMAGE FIRE DETECTION
摘要
Abstract
Image fire detection is actually a binary classification problem of imbalanced data,existing technology often brings in new noise points or loses very important messages when dealing with the imbalanced data classification problems,and the stability in algorithm is also poor.Accord-ing to the advantage of Adaboost in assigning different weights to samples,plus the SVM has a better classification performance under equilibrium data condition,we propose the Adaboost-SVM algorithm by combining Adaboost algorithm with support vector machine (SVM).It takes the eigen-value of suspected flame area as the input parameter of SVM classifier,intensively marks the fault samples with Adaboost algorithm,and sets the threshold value on sample weights,and reconstructs a few samples by adopting a certain criteria to reach the balance between positive and negative samples.At last,the algorithm outputs final classification results through voting mechanism when training data.Experimental results show that this algorithm improves the classification performance of fire when the distribution is imbalance between positive and negative samples.关键词
图像型火灾探测/不平衡数据/支持向量机/AdaboostKey words
Image fire detection/Imbalanced data/Support vector machine(SVM)/Adaboost分类
信息技术与安全科学引用本文复制引用
廖雨婷,王慧琴,柴茜,卢英,马宗方..Adaboost算法在图像型火灾探测中的应用研究[J].计算机应用与软件,2015,(4):153-155,180,4.基金项目
教育部高等学校博士学科点专项科研基金（20126120110008）；陕西省教育厅产业化项目（2011JG12）；陕西省自然科学基础研究计划项目（2012JQ8021）；教育厅专项科研项目（2013JK1144）。 （）
