Fire detection systems in ships are based on smoke and heat detection in accordance with safety regulations. The rapid advancement of machine vision technology has led to the development of video smoke detection (VSD) systems. In this study, a VSD system is applied to smoke detection within the engine room of the ship. A dataset for a range of scenarios was created with a smoke generator. The method for smoke detection was based on motion detection and a support vector machine classifier, which was used to make candidate regions and perform classification. A local binary pattern descriptor was used to extract the feature vector. A training set was made from a variety of video frames, randomly. Experimental results seldom produced false positive windows in the non-smoke region. However, if the greyscale value of difference image between background and the smoke is lower than the setting value for motion detection, the system could not detect smoke. Processing time is sufficiently fast for use in real-time smoke detection systems. To install a VSD system on-board a vessel, the authors recommend a performance standard of the system which must be met.

中文翻译：

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基于视频图像的船舶机舱烟雾检测

船上的火灾探测系统基于烟雾和热量探测，符合安全法规。机器视觉技术的飞速发展导致视频烟雾检测（VSD）系统的发展。在这项研究中，将VSD系统应用于船舶机舱内的烟雾探测。使用烟雾生成器创建了一系列场景的数据集。烟雾检测方法基于运动检测和支持向量机分类器，用于分类候选区域并进行分类。使用局部二进制模式描述符提取特征向量。训练集是由各种视频帧随机组成的。实验结果很少在非烟区域产生假阳性窗口。然而，如果背景和烟雾之间的差异图像的灰度值低于运动检测的设置值，则系统无法检测到烟雾。处理时间足够快，可用于实时烟雾探测系统。为了在船上安装VSD系统，作者建议必须满足该系统的性能标准。