Name
Abstract | ||
|---|---|---|
We develop a probabilistic color distance measure based on hypothesis testing in order to achieve shading invariance in image segmentation. We derive this new color distance measure based on the Dichromatic Reflection Model and noise statistics. We show preliminary results of using the new semi-metric in a color image segmentation task to show its effectiveness. |
Year | Venue | Keywords |
|---|---|---|
2007 | EUSIPCO | image colour analysis,image segmentation,probability,dichromatic reflection model,color image segmentation task,hypothesis testing,noise statistics,probabilistic shading invariant color distance measure,color,euclidean distance,colored noise,probabilistic logic |
Field | DocType | ISBN |
Computer vision,Scale-space segmentation,Color histogram,Pattern recognition,Image segmentation,Color balance,Artificial intelligence,Color difference,Color normalization,Color quantization,Mathematics,Color image | Conference | 978-839-2134-04-6 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Slawo Wesolkowski | 1 | 36 | 5.55 |
| Paul W. Fieguth | 2 | 612 | 54.17 |