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 in | 2011 International Conference on Document Analysis and Recognition pp. 864 - 869 |
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| Main Authors | , , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.09.2011
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| Subjects | |
| Online Access | Get full text |
| ISBN | 1457713500 9781457713507 |
| ISSN | 1520-5363 |
| DOI | 10.1109/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. |
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| 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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| 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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| 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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