Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICDAR.2011.177 | ICDAR-1 |
Keywords | Field | DocType |
architecture,image processing,architectural floor plans,automated floor plan analysis,convex hull,improved automatic analysis,room recognition,architectural floor plan analysis | Reference data (financial markets),Graphics,Computer vision,Computer graphics (images),Computer science,Floor plan,Image processing,Convex hull,Image segmentation,Preprocessor,Artificial intelligence,Semantics | Conference |
ISSN | Citations | PageRank |
1520-5363 | 15 | 0.71 |
References | Authors | |
16 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sheraz Ahmed | 1 | 105 | 28.32 |
| Marcus Liwicki | 2 | 1292 | 101.35 |
| Markus Weber | 3 | 166 | 20.97 |
| Andreas Dengel | 4 | 1926 | 280.42 |