Technical Papers Session IV: Skin detection based pornography filtering using adaptive back propagation neural network
Abstract/Description
As the internet becomes faster and cheaper, its misuses like pornographic production and consumption has also been increased. Pornography is considered a sensitive issue to discuss openly in our society and this is a neglected one too. Psychological research says that Pornographic and nude images create a negative impact on the viewer's mind. And also watching pornography is a kind of addiction too. At the first stage, such people create distance from their loved ones which leads them to depression and on extreme stages they could be involved in many types of criminal activities. In this article, the Skin Detection based Pornographic Filtering using Adaptive Back Propagation Neural Network (SD-PFT-ABPNN) Technique is presented. The Simulation results of Proposed SD-PFT-ABPNN techniques shown desirable results regarding MMSE and regression as compared to conventional skin detection-based Porn Filtering Techniques using Global Image Enhancement (PFTGIE), Porn Filtering Techniques Without using Global Image Enhancement (PFTWGIE) techniques. When the results were compared, it was seen that the BR algorithm has the highest accuracy rate with 99.70%.
Keywords
Pornography, PFT, Complexity, PFTGIE, PFTWGIE, Pornography detection
Location
Lecture Hall A (Aman Tower, 12th floor)
Session Theme
Technical Papers Session IV - Artificial Intelligence
Session Type
Parallel Technical Session
Session Chair
Engr. Parkash Lohana
Start Date
17-11-2019 3:00 PM
End Date
17-11-2019 3:20 PM
Recommended Citation
Farooq, M. S., Khan, M. A., Abbas, S., Athar, A., Ali, N., & Hassan, A. (2019). Technical Papers Session IV: Skin detection based pornography filtering using adaptive back propagation neural network. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2019/2019/35
COinS
Technical Papers Session IV: Skin detection based pornography filtering using adaptive back propagation neural network
Lecture Hall A (Aman Tower, 12th floor)
As the internet becomes faster and cheaper, its misuses like pornographic production and consumption has also been increased. Pornography is considered a sensitive issue to discuss openly in our society and this is a neglected one too. Psychological research says that Pornographic and nude images create a negative impact on the viewer's mind. And also watching pornography is a kind of addiction too. At the first stage, such people create distance from their loved ones which leads them to depression and on extreme stages they could be involved in many types of criminal activities. In this article, the Skin Detection based Pornographic Filtering using Adaptive Back Propagation Neural Network (SD-PFT-ABPNN) Technique is presented. The Simulation results of Proposed SD-PFT-ABPNN techniques shown desirable results regarding MMSE and regression as compared to conventional skin detection-based Porn Filtering Techniques using Global Image Enhancement (PFTGIE), Porn Filtering Techniques Without using Global Image Enhancement (PFTWGIE) techniques. When the results were compared, it was seen that the BR algorithm has the highest accuracy rate with 99.70%.