Name
Abstract | ||
|---|---|---|
Over the last thirty years evaluation of texture analysis algorithms has been dominated by two databases: Brodatz has typically been used to provide single images of approximately 100 texture classes, while CUReT consists of multiple images of 61 physical samples captured under a variety of illumination conditions. While many highly successful approaches have been developed for classification, the challenging question of measuring perceived inter-class texture similarity has rarely been addressed. In this paper we introduce a new texture database which includes a collection of 334 samples together with perceptual similarity data collected from experiments with 30 human observers. We have tested four of the leading texture algorithms and they provide accurate (approximate to 100%) performance in a CUReT style classification task, however, a second experiment shows that resulting inter-class distances do not correlate well with the perceptual data. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.5244/C.25.120 | PROCEEDINGS OF THE BRITISH MACHINE VISION CONFERENCE 2011 |
Field | DocType | Citations |
De facto standard,Computer vision,Pattern recognition,Computer science,Matrix (mathematics),Segmentation,Artificial intelligence,Perceptual similarity | Conference | 12 |
PageRank | References | Authors |
0.69 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alasdair D. F. Clarke | 1 | 56 | 3.94 |
| Fraser Halley | 2 | 24 | 2.10 |
| Andrew J. Newell | 3 | 89 | 4.81 |
| Lewis D. Griffin | 4 | 381 | 45.96 |
| m j chantler | 5 | 148 | 24.14 |