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| Content Provider | IET Digital Library |
|---|---|
| Author | Zhang, Jing Sui, Lei Zhuo, Li Li, Zhenwei |
| Abstract | According to biological attention mechanism, a region of interest (ROI) detection based on visual attention model is closer to human visual system. Taken into account the characteristics of pornographic image during regions detection, a pornographic image region detection method based on visual attention model in compressed domain is proposed in this study, which includes the following four steps: (i) the skin colour regions of pornographic images are detected in compressed domain; (ii) visual saliency map in compressed domain is computed to construct visual attention model; (iii) threshold segmentation method is used for visual saliency map, and then the torso information is retained as pornographic regions; and (iv) four features of colour, texture, intensity and skin are extracted to represent pornographic region. The experimental results show that the proposed method can perform well on the speed/accuracy of pornographic regions detection and representation. |
| Starting Page | 384 |
| Ending Page | 391 |
| Page Count | 8 |
| ISSN | 17519659 |
| Volume Number | 7 |
| e-ISSN | 17519667 |
| Issue Number | Issue 4, Jun (2013) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/7/4 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2012.0381 |
| Journal | IET Image Processing |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Biological Attention Mechanism Compressed Domain Computer Vision And Image Processing Technique Human Visual System Image And Video Coding Image Coding Image Colour Analysis Image Intensity Image Representation Image Segmentation Image Texture Object Detection Pornographic Image Region Detection Pornographic Region Representation Region of Interest Detection ROI Detection Skin Colour Region Threshold Segmentation Method Torso Information Visual Attention Model Visual Saliency Map |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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