A study on the flame detection and object classification technique using the color information

Min-Gu Kim, S. Pan
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引用次数: 4

Abstract

With the development of construction techniques, the high-rise buildings have been established and populated. In the event of fire in these buildings, as the fire is spreading, the risk of large fire is increased and the resulting casualties and property damages are increased. Therefore, the techniques to detect the flame at an early stage are necessary in order to prevent the fire and minimize the damage. The flame detection technique based on physical sensor has limited disadvantages in detecting the fire early. In addition, this technique has a problem of increasing the cost in proportion to the number of regions where it is installed. Image-based flame detection technique has been studied to complement these problems. In this paper, the object is detected by using the adaptive background modeling technique. In the flame detection technique, the flame is detected by converting RGB images to HSI images which have strength even in the change of lightings or scenes. Also, if the object with similar color to the flame is detected from the output image, it will detect it as a fire, leading to increase the misdetection problem. To solve these problems, objects are classified by using the direction information of the object detected. Based on experiment results, if the flame is detected only using the color information, it is confirmed that the fire is detected in real time. However, the problem of classifying the object as the fire occurred when the object had the similar color to the flame in the image. For this, it is confirmed that the performance was improved when classifying the object using the direction information of the object.
基于颜色信息的火焰检测与目标分类技术研究
随着建筑技术的发展,高层建筑的建立和发展。这些建筑物一旦发生火灾,随着火势的蔓延,发生大火的风险加大,造成的人员伤亡和财产损失也随之增加。因此,为了防止火灾的发生和减少损失,早期发现火焰的技术是必要的。基于物理传感器的火焰探测技术在早期发现火灾时有一定的局限性。此外,该技术还存在一个问题,即成本会随着安装区域数量的增加而增加。针对这些问题,研究了基于图像的火焰检测技术。本文采用自适应背景建模技术对目标进行检测。在火焰检测技术中,通过将RGB图像转换为HSI图像来检测火焰,这种图像即使在光线或场景的变化中也具有强度。此外,如果从输出图像中检测到与火焰颜色相似的物体,则会将其检测为火焰,从而增加了误检问题。为了解决这些问题,利用检测到的目标方向信息对目标进行分类。根据实验结果,如果仅利用颜色信息检测火焰,则可以确定火焰是实时检测到的。然而,当物体的颜色与图像中的火焰相似时,就会出现将物体分类为火焰的问题。为此,证实了利用目标的方向信息对目标进行分类时,性能得到了提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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