Design and Development of Real-Time Image Based Fire Detection Using OpenCV and HSV

Nowadays fire detection and recognition are one of the major securities and security region for saving human life. Concern to this we are going to propose a new model for early detection and recognition of the fire for the purpose to provide the better services. In this proposed model we are going to use The OpenCV and HSV driven Fire Detection initiative is aimed at recognizing fires by utilizing image processing technology to give early alerts to people. This proposed system is launched to overcome limitations like enhance efficiency and instant alert to avoid disastrous situation through. The existing automated fire alarm systems like the sensor method have limitations in detecting smoke-caused fires in restricted areas and late alerts. By employing a central processing unit and connecting a webcam as hardware, video footage from the surroundings is captured in the form of image as an input source. The components of theory emphasize computer vision, deep learning, image processing, color models, and the algorithm operation for detecting fires. This endeavor is designed to offer a comprehensive understanding of object detection using computers and the flexibility of these technologies in various applications. The utilization of OpenCV serves the purpose of computer vision in this system. The complete code is written in Python language utilizing the open CV library.