Name
Abstract | ||
|---|---|---|
In this paper the obscene images first primarily recognizes through the human skin color detection and key point model matching. The other images that are not confirmed extract characteristic of obscene images through edge detection, posture estimation and wavelet compression, and then recognized using the optimizing broaden weighted fuzzy neural network, which is called two-phase recognizing method. The experiment indicates the method that this paper present can recognize the obscene images effectively. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11427445_48 | ISNN (2) |
Keywords | Field | DocType |
fuzzy neural network,edge detection,obscene image recognition,obscene image,posture estimation,key point model matching,human skin color detection,wavelet compression,paper present,image recognition | Model matching,Computer vision,Color detection,Image sensor,Pattern recognition,Computer science,Edge detection,Model-based reasoning,Fuzzy neural nets,Artificial intelligence,Artificial neural network,Wavelet transform | Conference |
Volume | ISSN | ISBN |
3497 | 0302-9743 | 3-540-25913-9 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaohua Liu | 1 | 18 | 2.16 |
| Zhezhou Yu | 2 | 22 | 5.50 |
| Libiao Zhang | 3 | 34 | 7.03 |
| Miao Liu | 4 | 6 | 1.25 |
| Chunguang Zhou | 5 | 543 | 52.37 |
| Chunxia Li | 6 | 4 | 1.22 |
| Catitang Sun | 7 | 0 | 0.34 |
| Li Zhang | 8 | 272 | 42.02 |