Name
Abstract | ||
|---|---|---|
In this paper, we present an approach for symbol representation and recognition in line drawings, integrating both the vector-based structural description and pixel-level statistical features of the symbol. For the former, a vectorial template is defined on the basis of the vectorization model and exploited in segmenting symbols from the line network. For the latter, a Radon-transform-based signature is employed to characterize shapes on the symbol and the components level. Experimental results on real technical drawings are presented to show the promising aspect of our approach. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICPR.2010.466 | ICPR |
Keywords | Field | DocType |
image representation,pixel-level features,vector-based structural description,radon-transform,line drawings,statistical analysis,real technical drawing,image recognition,symbol recognition,vectorial features,components level,line network,vectorization model,symbol representation,radon transform,radon transforms,line drawing,symbol recognition combining vectorial,vectorial template,pixel-level statistical features,promising aspect,pixel-level statistical feature,radon-transform-based signature,pixel,pattern recognition,shape,image segmentation | Computer vision,Technical drawing,Symbol recognition,Pattern recognition,Computer science,Symbol,Image representation,Vectorization (mathematics),Artificial intelligence,Pixel,Radon transform,Line drawings | Conference |
ISSN | ISBN | Citations |
1051-4651 | 978-1-4244-7542-1 | 3 |
PageRank | References | Authors |
0.40 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feng Su | 1 | 170 | 18.63 |
| tong lu | 2 | 372 | 67.17 |
| Ruoyu Yang | 3 | 47 | 6.47 |