Name
Abstract | ||
|---|---|---|
This paper presents a novel dynamic threshold approach to discriminate skin pixels and non-skin pixels in colour images. Fixed decision boundaries (or fixed threshold) classification approaches are successfully applied to detect human skin tone in colour images. These fixed thresholds mostly failed in two situations as they only search for a certain skin colour range: any non-skin object may be classified as skin if non-skin objects|s colour values belong to fixed threshold range; any true skin may be mistakenly classified as non-skin if the skin colour values do not belong to fixed threshold range. Therefore in this paper, instead of predefined fixed thresholds, novel online learned dynamic thresholds are used to overcome the above drawbacks. The experimental results show that our method is robust in overcoming these drawbacks. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1504/IJBM.2012.044291 | IJBM |
Keywords | Field | DocType |
skin tone detection, dynamic threshold | Computer vision,Economics,Pixel,Artificial intelligence,Skin tone | Journal |
Volume | Issue | ISSN |
4 | 1 | 1755-8301 |
Citations | PageRank | References |
5 | 0.42 | 19 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yogarajah Pratheepan | 1 | 5 | 1.10 |
| J. V. Condell | 2 | 384 | 29.15 |
| kevin curran | 3 | 831 | 96.66 |
| Paul McKevitt | 4 | 18 | 3.64 |
| Abbas Cheddad | 5 | 268 | 17.93 |