Flood Tracking in Severe Weather

Severe weather conditions greatly impair the performance of outdoor imaging. In this study, two region-based image segmentation methods, Grow Cut and Region Growing (RegGro), were applied to rain scenes. This study demonstrates that segmentation accuracy depends on fog and rain stains. In severe rainfall periods, heavy rain and fog reduced the overall image quality, and both methods yielded segmentation failure. The results show that both region-based methods are effective for segmenting objects in images captured under poor weather conditions. Both methods have unique advantages and disadvantages for fog and stain conditions. The segmentation accuracy yielded by the Grow Cut and RegGrow methods was 75% and 85%, respectively.