A comparative study of road extraction techniques from aerial imagery - a navigational perspective

The problem of road extraction from satellite or aerial imagery remains one of the most complex and challenging yet crucial in image processing. The review covers road extraction methods such as mathematical morphology, road tracking and modelling, texture progressive analysis, clustering, graph cuts, normalised cuts, tensor voting, artificial neural networks, support vector machines, snakes and level sets. Among criteria upon which algorithms are analysed are level of automation, ability to incorporate a priori knowledge and inclusion of road parameters (geometric, radiometric, textural, spatial) and type of output information etc. The study explores and compares the potential of individual state-of-the-art extraction algorithms and their combinations satisfying the stated requirements to facilitate future development of generic feature extraction algorithms for real-time application in visual aerial navigation systems. The survey is supported by a tabulated summary that details the operational peculiarities and output forms of each processing technique and compares their advantages and disadvantages.

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