Improved Automatic Analysis of Architectural Floor Plans

This paper proposes a novel complete system for automated floor plan analysis. Besides applying and improving state-of-the-art processing methods, we introduce novel preprocessing methods, e.g., the differentiation between thick, medium, and thin lines and the removal of components outside the conve...

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Published in2011 International Conference on Document Analysis and Recognition pp. 864 - 869
Main Authors Ahmed, S., Liwicki, M., Weber, M., Dengel, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2011
Subjects
Online AccessGet full text
ISBN1457713500
9781457713507
ISSN1520-5363
DOI10.1109/ICDAR.2011.177

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Abstract This paper proposes a novel complete system for automated floor plan analysis. Besides applying and improving state-of-the-art processing methods, we introduce novel preprocessing methods, e.g., the differentiation between thick, medium, and thin lines and the removal of components outside the convex hull of the outer walls. Especially the latter method increases the performance of the final system. In our experiments on a reference data set we compare our approach to other approaches available in the literature. We show that our system outperforms previous systems. The final room recognition accuracy is 79% that is 10% higher than the 69% achieved by a state-of-the-art approach from the literature.
AbstractList This paper proposes a novel complete system for automated floor plan analysis. Besides applying and improving state-of-the-art processing methods, we introduce novel preprocessing methods, e.g., the differentiation between thick, medium, and thin lines and the removal of components outside the convex hull of the outer walls. Especially the latter method increases the performance of the final system. In our experiments on a reference data set we compare our approach to other approaches available in the literature. We show that our system outperforms previous systems. The final room recognition accuracy is 79% that is 10% higher than the 69% achieved by a state-of-the-art approach from the literature.
Author Weber, M.
Ahmed, S.
Liwicki, M.
Dengel, A.
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  fullname: Dengel, A.
  email: Andreas.Dengel@dfki.de
  organization: Knowledge Manage. Dept., German Res. Center for AI (DFKI), Kaiserslautern, Germany
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Snippet This paper proposes a novel complete system for automated floor plan analysis. Besides applying and improving state-of-the-art processing methods, we introduce...
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StartPage 864
SubjectTerms Accuracy
architectural floor plan analysis
Floors
Graphics
Image edge detection
Image segmentation
Semantics
Title Improved Automatic Analysis of Architectural Floor Plans
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