# Multi-Scale Flame Situation Detection Based on Pixel-Level Segmentation of Visual Images
## 1 Introduction  
Fire is a pervasive and hazardous threat that poses significant risks to public safety and social progress. For example, for high-rise buildings with dense populations, fires cause incalculable damage to the personal and property safety of residents. Forest fires engender substantial economic losses, air pollution, environmental degradation, and risks to both humans and animals. As shown in Figure 1, typical fire incidents include the Australian forest fires, the Notre Dame Cathedral fire, the parking shed fire in Shanghai, China, and the industrial plant fire in Anyang, China. Australia experienced devastating wildfires lasting for several months between July 2019 and February 2020, claiming the lives of 33 individuals and resulting in the death or displacement of three billion animals. On 22 December 2022, a sudden fire engulfed a parking shed in a residential area in Shanghai, resulting in the destruction of numerous vehicles. In secure areas such as residential housing, flames appear seconds after vehicle short circuits or malfunctions. Within approximately three minutes, the flame temperature can escalate to 1200 \({}^{\circ}\)C. High-temperature toxic gases rapidly permeate corridors and rooms, causing people to suffocate to death. Shockingly,a vehicle fire takes a person's life in as little as 100 s. Therefore, efficient fire prevention and control measures can effectively reduce casualties and property losses. Fire situation information plays a crucial role in guiding fire rescue operations by providing essential details such as the fire location, fire area, and fire intensity. As shown by the flame temperature data captured by sensors [1], shown in the subsequent Figure 2a, the evolution of a fire typically encompasses three distinct stages: the fire initiation stage, violent burning stage, and decay extinguishing stage. During the stage of fire initiation, the flame burns locally and erratically, accompanied by relatively low room temperatures. This phase presents an opportune time to effectively put out the fire. In the violent burning stage, the flame spreads throughout the entire room, burning steadily and causing the room temperature to rapidly rise to approximately 1000 \({}^{\circ}\)C. Extinguishing the fire becomes challenging during this stage. In the decay stage, combustible materials are consumed, and fire suppression efforts take effect. However, it is crucial to note that the fire environment undergoes rapid and dynamic changes during these stages. This renders traditional sensor-based detectors inadequate, primarily due to limitations in detection distance and susceptibility to false alarms triggered by factors such as light and dust. Moreover, these detectors are incapable of providing a visual representation of the fire scene, hindering comprehensive situational awareness. Figure 1: Process of dealing with fire incidents. Figure 2: Flame parameters trends during combustion. Based on two fire videos captured in the experimental scenario, flame parameters for both fire processes were computed. Similar to the sensor-based approach, flame parameters derived from visual data exhibit a three-stage combustion pattern. It is evident that the vision-based fire detection method can be extended to respond rapidly to real-world fire incidents. Fire detection technology based on visual images offers inherent advantages. On the one hand, the portability and anti-interference of camera equipment enhance the reliability of visual fire detection. On the other hand, fire situation parameters derived from visual methods such as the flame height, width, and area are significant to fire detection and control [2]. Figure 2 illustrates the acquisition of flame situation parameters through visual fire detection technology. In the upper part of Figure 2, video_1 and video_2 represent two fire video sequences obtained in the experimental scene, in which the images were acquired through the acquisition device in Figure 3a.