Image Segmentation and Target Tracking using Computer Vision

Abstract: In this master thesis the possibility of detecting and tracking objects in multispectral infrared video sequences is investigated. The current method  with fix-sized rectangles have significant disadvantages. These disadvantages will be solved using image segmentation to estimate the shape of the object. The result of the image segmentation is used to determine the infrared contrast of the object. Our results show how some objects will give very good segmentation, tracking as well as shape detection. The objects that perform best are the flares and countermeasures. But especially helicopters seen from the side, with significant movements, is better detected with our method. The motion of the object is very important since movement is the main component in successful shape detection. This is so because helicopters are much colder than flares and engines. Detecting the presence and position of moving objects is easier and can be done quite successfully even with helicopters. But using structure tensors we can also detect the presence and estimate the position for stationary objects.