The fire detection system is a security system. The primary function of this system is to detect fires and turn on alarms to warn of fire accidents. This system is written in Python with an OpenCV computer vision module. It uses the HSV color algorithm to detect fires.
This project provides a computer vision-based technique for detecting fire and identifying hazardous fires by processing the video data generated by an ordinary camera.
- Python
- OpenCV
- SMTPLIB
- HSV color Algorithm
Color isolation can be achieved by extracting a particular HSV (hue, saturation, value) from an image. The algorithm is simple and the main steps are as follows:
- Step 1 - RGB to HSV Conversion
- Step 2 - Apply a Threshold Mask
We want to convert the image to HSV because working with HSV values is much easier to isolate colors. In the HSV representation of color, hue determines the color you want, saturation determines how intense the color is and value determines the lightness of the image. As can be seen in the image below, 0 on the wheel would specify a mild red color and 240 would specify a blue color.
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Install playsound
pip install playsound -
Install OpnCV
pip install opencv-python
python fire-detector.py
