Segmentation of Building Facade Towers

  • Gayane ShaluntsEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9475)


Architectural styles are phases of development that classify architecture in the sense of historic periods, regions and cultural influences. The article presents the first approach, performing automatic segmentation of building facade towers in the framework of an image-based architectural style classification system. The observed buildings, featuring towers, belong to Romanesque, Gothic and Baroque architectural styles. The method is a pipeline unifying bilateral symmetry detection, graph-based segmentation approaches and image analysis and processing technique. It employs the specific visual features of the outstanding architectural element tower - vertical bilateral symmetry, raising out of the main building and solidity. The approach is robust to high perspective distortions. It comprises two branches, targeting facades with single and double towers correspondingly. The performance evaluation on a vast number of images reports extremely high segmentation precision.


Bilateral Symmetry Foreground Pixel Architectural Style Architectural Element Image Mask 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.SAIL LABS Technology GmbHViennaAustria

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