An algorithm which estimates the extent of flood from random, crowd sourced images is proposed. It uses color based segmentation with brown color to segment out the flood water. The average brown color intensity, largest brown area, as well as water depth found out by comparison with human bodies detected, together contribute to the final estimation of the extent of flood. The algorithm, since it deals with normal images rather than satellite images or video sequences, can be used widely to explore flood affected areas so that adequate help can be supplied. This method can also be used in flood detection systems run in order to carry out rescue operations enabling us to lend our support for flood victims. Moreover, the fact that the existing work in this area deals with videos and satellite images mainly adds to the novelty of this work.
M. Geetha, Manoj, M., Sarika, A. S., Mohan, M., and Rao, S. N., “Detection and estimation of the extent of flood from crowd sourced images”, in 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2017.