Name
Abstract | ||
|---|---|---|
Whenever an image database has to be organised according to higher level human perceptual properties, a transformation model is needed to bridge the semantic gap between features and the perceptual space. To guide the feature selection process for a transformation model, we investigate the behaviour of 5 texture feature categories.Using a novel mixed synthesis algorithm we generate textures with a gradual transition between two existing ones, to investigate the feature interpolation behaviour. In addition the features' robustness to minor textural changes is evaluated in a kNN query-by-example experiment.We compare robustness and interpolation behaviour, showing that Gabor energy map features are outperforming gray level co-occurrence matrix features in terms of linear interpolation quality. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-03767-2_140 | CAIP |
Keywords | Field | DocType |
higher level,gray level co-occurrence matrix,gabor energy map feature,quantitative evaluation,feature selection process,texture feature category,linear interpolation quality,human perceptual property,transformation model,interpolation behaviour,texture feature robustness,feature interpolation behaviour,linear interpolation,semantic gap,query by example,feature selection | Gradual transition,Computer vision,Feature selection,Pattern recognition,Matrix (mathematics),Computer science,Interpolation,Semantic gap,Robustness (computer science),Artificial intelligence,Linear interpolation,Texture synthesis | Conference |
Volume | ISSN | Citations |
5702 | 0302-9743 | 5 |
PageRank | References | Authors |
0.50 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefan Thumfart | 1 | 44 | 2.37 |
| Wolfgang Heidl | 2 | 103 | 7.01 |
| Josef Scharinger | 3 | 215 | 44.43 |
| Christian Eitzinger | 4 | 164 | 15.33 |