基于加速鲁棒特征和支持向量机的视觉火灾探测系统

2018 6th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2018-05-01 DOI:10.1109/ICOICT.2018.8528752

Laela Citra Asih, F. Sthevanie, Kurniawan Nur Ramadhani

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引用次数: 1

摘要

本文提出了一种利用摄像机拍摄的视频进行火灾探测的系统。在三个正交平面上采用加速鲁棒特征(SURF)提取特征来获取图像的时空特征。我们使用支持向量机(SVM)算法将特征分类为火或非火对象。采用SURF阈值0、聚类数5和高斯SVM核，系统生成准确率为81.25%。

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Visual Based Fire Detection System Using Speeded Up Robust Feature and Support Vector Machine

This paper proposed a fire detection system using video captured from camera. We built the system using Speeded Up Robust Feature (SURF) feature extraction on three orthogonal plane to obtain the spatial and temporal features. We used Support Vector Machine (SVM) algorithm to classify the features as the fire or non-fire object. Using SURF threshold value 0, number of cluster 5 and gaussian SVM kernel, the system generated accuracy 81,25%.

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2018 6th International Conference on Information and Communication Technology (ICoICT)

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