Region-based Pornographic Image Detection

• Published in: 2005 IEEE 7th Workshop on Multimedia Signal Processing pp. 1 - 4
• Main Authors: Yuan Xu, Bin Li, Xiangyang Xue, Hong Lu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2005
• Subjects: arbitrary-shaped region feature; Feature extraction; Image classification; Image segmentation; Information filtering; Information filters; Information processing; Intelligent networks; Laboratories; ponorgraphic image detection; Quantization; Skin; skin detection
• ISBN: 0780392884; 9780780392885
• DOI: 10.1109/MMSP.2005.248675

Recent advantages in digital images and networks have made pornographic images more accessible than ever. Methods of detecting pornographic images have been proposed in some existing work. However, the skin detection modules adopted are all pixel-based and skin region shape features are rarely properly used. This paper presents a framework for pornographic image detection based on skin region information. Different from traditional works, our approach extracts color and texture features from arbitrary-shaped segmented regions. Then Gaussian mixture models are built for skin and non-skin region classification, and the skin map is produced based on the classification result. Finally, eigenregion features are used to describe the layout of skin regions on the whole image and pornographic images are detected according to the skin modality