Name
Abstract | ||
|---|---|---|
We describe a similarity based adult image detection technique (SID) exploiting composed MPEG-7 visual descriptors. The technique with a large set of training adult image database and a smaller set of training non-adult image database is practically useful in detecting adult images with little false negatives. SID achieved 99% correct detections with 23% false positives when experimented with a database containing 1,300 training non-adult images, and 93.5% correct detections with 8.4% false positives when experimented with a database containing 12,000 training non-adult images. 9,900 training adult images are used for both experiments. Given a query, ten most similar images are retrieved. If majority of the retrieved are adult images, then the query is determined to be an adult image. Otherwise, it is determined to be a non-adult image. SID can detect adult Internet content with the aid of text filtering system as described in the later section. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-45036-X_75 | Human.Society.Internet |
Keywords | Field | DocType |
similar image,training adult image,correct detection,training adult image database,false positive,adult internet content,non-adult image,adult image detection technique,training non-adult image,mpeg-7 visual descriptors,adult image | Computer vision,Image sensor,Computer science,Image detection,Image retrieval,Filter (signal processing),Artificial intelligence,Visual descriptors,Image database,False positive paradox,The Internet | Conference |
Volume | ISSN | ISBN |
2713 | 0302-9743 | 3-540-40456-2 |
Citations | PageRank | References |
3 | 0.42 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seong-Joon Yoo | 1 | 102 | 16.88 |
| Minho Jung | 2 | 11 | 2.49 |
| Hee Beom Kang | 3 | 3 | 0.42 |
| Chee Sun Won | 4 | 573 | 87.74 |
| Soo-Mi Choi | 5 | 59 | 17.56 |