Loading

Detection of Fire Regions from a Video Image Frames in YCbCr Color Model
Yumnam Kirani Singh1, Debasish Deb2

1Yumnam Kirani Singh, C-DAC Silchar, Silchar, India.
2Debasish Deb, C-DAC Silchar, Silchar, India.

Manuscript received on 04 August 2019. | Revised Manuscript received on 09 August 2019. | Manuscript published on 30 September 2019. | PP: 6082-6086 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5637098319/2019©BEIESP | DOI: 10.35940/ijrte.C5637.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Proposed here is a fire region detection method from a recorded video captured during the occurrence of fire. This method is based only on the chrominance components of the YCbCr color model. To distinguish the fire-region in an image frame of fire video containing the fire region, the difference between Cr and Cb is computed. The difference is enhanced by computing the square of it and then normalize range of difference squared to 0 to 255. It is then binarized at using automatic thresholding method to segment the fire region from the non-fire region. The fire region in the binary is located using the connected component analysis and the region is mapped to the original image frames of the fire video. We have tested the method in the actual fire video and it is found that the method can appropriately locate the fire regions in every image frame of the video. The method is simple and fast and hence can be used to forest fire monitoring using drones.
Keywords: Chrominance, Color Model, Fire-Region Detection, Forest Fire Detection, RGB, YCbCr.

Scope of the Article:
Image Security