Automatic Detection of Human Nudes
International Journal of Computer Vision - 1998 Marr Prize
Statistical color models with application to skin detection
International Journal of Computer Vision
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Introduction to MPEG-7: Multimedia Content Description Interface
Introduction to MPEG-7: Multimedia Content Description Interface
Recognition of Pornographic Web Pages by Classifying Texts and Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
An adult image identification system employing image retrieval technique
Pattern Recognition Letters
Semi-supervised kernel density estimation for video annotation
Computer Vision and Image Understanding
Unified video annotation via multigraph learning
IEEE Transactions on Circuits and Systems for Video Technology
Beyond distance measurement: constructing neighborhood similarity for video annotation
IEEE Transactions on Multimedia - Special section on communities and media computing
Filtering adult image content with topic models
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Active learning in multimedia annotation and retrieval: A survey
ACM Transactions on Intelligent Systems and Technology (TIST)
Towards a Relevant and Diverse Search of Social Images
IEEE Transactions on Multimedia
System for screening objectionable images
Computer Communications
Hi-index | 0.08 |
In this paper, a novel and effective pornographic image recognition method is proposed. Contributions of this paper include two aspects. (1) Due to the fact that the images are mostly stored and transmitted with JPEG compressed format on Internet, feature extraction is directly performed in the compressed domain. The exacted features include those derived from skin color regions, the results of image retrieval, human face and region of interest, as well as the global features of color and texture. (2) Data mining method is employed to search for the potential decision rules from large-scale image feature sets. Taken the misclassification cost and test cost into account, multi-cost sensitive decision tree is constructed first to improve the recognition speed and accuracy. Furthermore, the concept of pornography degree is introduced into the decision rules, which is output as the recognition results to represent the probability of the image being judged as pornographic. Experimental results show that, the recognition speed of the proposed method is almost three times faster than the classical pixel domain-based recognition method, and the recognition accuracy is also higher in terms of True Alarm Rate (TPR) and False Alarm Rate (FPR).