Recognition of Weather in an Outdoor Stationary Camera View

This thesis deals with classification of weather from stationary outdoor camera images with a landscape view. It classifies fog, clear, partly cloudy and overcast weather in particular. The problem was solved by computing five image flags and using machine learning. Hit rate of 95% was achieved with only small variances between weather types. The main finding of this work is that it is possible to successfully differentiate between the selected weather types with the chosen set of simple image flags. The implementation of this system enables plotting a graph of weather progression during a chosen day