Obstacles detection in foggy environment
نویسندگان
چکیده
In this paper, we propose a novel method of object detection in bad weather conditions like Fog and smoke. It is based on statistical model of dark channel prior to estimate the thickness of the haze and physics based image restoration approach. Further applying simple image enhancement techniques improve the visibility of an obstacle in the line of sight. Using this prior with this imaging model help recover refined haze free image. Finally, moving objects are segmented by simple Kalman Filter background differencing algorithm. Experimental results show that our method can be applied for building Intelligent Surveillance System to detect moving objects accurately due to low scene visibility. Moreover, a high quality depth map can also be obtained as a by-product of haze removal.
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