A Probabilistic Feature Fusion for Building Detection in Satellite Images

Dimitrios Konstantinidis, Tania Stathaki, Vasileios Argyriou, Nikos Grammalidis
2015 Proceedings of the 10th International Conference on Computer Vision Theory and Applications  
Building segmentation from 2D images can be a very challenging task due to the variety of objects that appear in an urban environment. Many algorithms that attempt to automatically extract buildings from satellite images face serious problems and limitations. In this paper, we address some of these problems by applying a novel approach that is based on the fusion of Histogram of Oriented Gradients (HOG), Normalized Difference Vegetation Index (NDVI) and Features from Accelerated Segment Test
more » ... ST) features. We will demonstrate that by taking advantage of the multi-spectral nature of a satellite image and by employing a probabilistic fusion of the aforementioned features, we manage to create a novel methodology that increases the performance of a building detector compared to other state-of-the-art methods. 205 Konstantinidis D., Stathaki T.
doi:10.5220/0005260502050212 dblp:conf/visapp/KonstantinidisS15 fatcat:qclixfvnfvehpivgl4ywuyn2di