컬러와 동적 특징을 이용한 화재의 시각적 감지 = Visual Sensing of Fires Using Color and Dynamic Features

다국어 초록 (Multilingual Abstract)

Fires are the most common disaster and early fire detection is of great importance to minimize the consequent damage. Simple sensors including smoke detectors are widely used for the purpose but they are able to sense fires only at close proximity. Recently, due to the rapid advances of relevant technologies, vision-based fire sensing has attracted growing attention. In this paper, a novel visual sensing technique to automatically detect fire is presented. The proposed technique consists of multiple steps of image processing: pixel-level, block-level, and frame level. At the first step, fire flame pixel candidates are selected based on their color values in YIQ space from the image of a camera which is installed as a vision sensor at a fire scene. At the second step, the dynamic parts of flames are extracted by comparing two consecutive images. These parts are then represented in regularly divided image blocks to reduce pixel-level detection error and simplify following processing. Finally, the temporal change of the detected blocks is analyzed to confirm the spread of fire. The proposed technique was tested using real fire images and it worked quite reliably.

참고문헌 (Reference)

1 S. Verstockt, "State of the art in vision-based fire and smoke detection" 2 : 285-292, 2009

2 R. Yang, "Real time 3D hand tracking for 3d modelling applications" 2011

3 W. Phillips, "Flame recognition in video" 224-229, 2000

4 L. Ma, "Fire smoke detection in video images using Kalman filter and Gaussian mixture color model" 484-487, 2010

5 H. Yamagishi, "Fire flame detection algorithm using a color camera" 255-260, 1999

6 S. Noda, "Fire detection in tunnels using an image processing method" 5742-, 1994

7 D. A. Ballard, "Computer Vision" Prentice-Hall 1982

8 J. R. Martinez-de Dios, "Automatic forest-fire measuring using ground stations and unmanned aerial systems" 11 : 6328-6353, 2011

9 G. Marbach, "An image processing technique for fire detection in video Images" 41 (41): 285-289, 2006

10 Wen-Bing Homg, "A new image-based real-time flame detection method using color analysis" 100-105, 2005

11 S. Y. Foo, "A machine vision approach to detect and categorize hydrocarbon fires in aircraft dry bays and engine compartments" 36 : 549-466, 2000

12 소방방재청, "2010년화재발생현황분석"