Vision-Based Algorithm for Fire Detection in Smart Buildings

  • Patel Abhilasha Paresh
  • Latha ParameswaranEmail author
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)


Recent technological advancement has opened the space for a gradual increase in the number of smart buildings. Public safety and security has becomes a matter of concern with such a development, especially in areas of fire accidents. The conventional fire detection system usually worked on sensors and takes time for fire detection. This work presents an early fire detection system that unlike conventional fire detection system is cost-effective with high fire detection rate. The proposed algorithm uses features like color, increase in area and intensity flicker for early detection of fire. Segmentation of fire colored regions is done with the help of L*a*b*, YCbCr, and RGB color space. Analysis of fire, i.e., fire area, its spread, temporal information, direction of the fire, and its average growth rate are measured using optical flow and blob analysis. Accuracy and F measure are used to evaluate the accuracy of the proposed system. Experimental results show that the average accuracy of the system is above 80% which is more promising in a video.


Fire detection system Color model Flicker Blob analysis Optical flow Lucas–Kanade 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAmrita School of Engineering, Amrita Vishwa VidyapeethamCoimbatoreIndia

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