Real-time precipitation suppression in video streams

In surveillance cameras rain and snow can introduce an unwelcome noise to the video stream. The resulting effect of the rain becomes bright streaks in the frames of the video. These streaks can disturb human viewers and image processing algorithms. Rain streaks can be hard to detect and remove as they are a very dynamic phenomenon dependent on camera settings and weather conditions. This thesis aims to research some already invented rain removal algorithms and compare and evaluate them. Surveillance cameras supply video in real-time so it is not possible to access the whole video and perform heavy computations relying on information from the future. Qualities such as level of streak suppression and time required to perform necessary calculations are weighed against each other

Challenges in video based object detection in maritime scenario using computer vision

This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here