Smoke detection in video using wavelets and support vector machines

被引：189

作者：

Gubbi, Jayavardhana ^{[1
]}

Marusic, Slaven ^{[1
]}

Palaniswami, Marimuthu ^{[1
]}

机构：

[1] Univ Melbourne, Dept Elect & Elect Engn, ISSNIP, Melbourne, Vic 3010, Australia

来源：

FIRE SAFETY JOURNAL | 2009年 / 44卷 / 08期

关键词：

Smoke detection; Wavelets; Support vector machine; Video processing; FIRE-DETECTION;

D O I：

10.1016/j.firesaf.2009.08.003

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Early warning systems are critical in providing emergency response in the event of unexpected hazards. Cheap cameras and improvements in memory and computing power have enabled the design of fire detectors using video surveillance systems. This is critical in scenarios where traditional smoke detectors cannot be installed. In such scenarios, it has been observed that the smoke is visible well before flames can be sighted. A novel method for smoke characterization using wavelets and support vector machines is proposed in this paper. Forest fire, tunnel fire and news channel videos have been used for testing the proposed method. The results are impressive with limited false alarms. The proposed algorithm is evaluated for its characterization properties using motion segmented images from a commercial surveillance system with good results. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：1110 / 1115

页数：6

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