Fire Detection in Still Image Using Color Model - Hira Lal Gope; Machbah Uddin; Shohag Barman; Dilshad Islam; Mohammad Khairul Islam (Institute of Advanced Engineering and Science, 2016)
Fire incidence is one of the major disasters of human society. This paper proposes a still image-based fire detection system. It has many advantages like lower cost, faster response, and large coverage. The existing methods are not able to detect fire region adequately. The proposed method overcome and addresses the issue. A binary contour image of flame that is capable of classifying fire or no fire in image for fire detection is proposed in this study. The color of fire area can range from red yellow to almost white. So, here it is challenges the detected area is actually fire or no fire. Our propose method consists of five parts. Firstly, the digital image is taken from dataset and the digital image is sampled and mapped as a grid of dots or picture elements. We convert image to separate RGB Color range Matrix. We define some rules to select yellow color range of the image later on converted the image to binary range. Finally, binary contour image of flame information that detect the fire. We have analyzed different types of fire images in different varieties and found accuracy 85-90%.