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Development of automatic obscene images filtering using deep learning

Awad, Abdelrahman Mohamed and Gunawan, Teddy Surya and Habaebi, Mohamed Hadi and Ismail, Nanang (2021) Development of automatic obscene images filtering using deep learning. In: Advances in Robotics, Automation and Data Analytics. Advances in Intelligent Systems and Computing, Chapter 5 . Springer, pp. 39-49. ISBN 978-3-030-70916-7

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Abstract

Because of Internet availability in most societies, access to pornography has be-come a severe issue. On the other side, the pornography industry has grown steadily, and its websites are becoming increasingly popular by offering potential users free passes. Filtering obscene images and video frames is essential in the big data era, where all kinds of information are available for everyone. This paper proposes a fully automated method to filter any storage device from obscene vid-eos and images using deep learning algorithms. The whole recognition process can be divided into two stages, including fine detection and focus detection. The fine detection includes skin color detection with YCbCr and HSV color spaces and accurate face detection using the Adaboost algorithm with Haar-like features. Moreover, focus detection uses AlexNet transfer learning to identify the obscene images which passed stage one. Results showed the effectiveness of our pro-posed algorithm in filtering obscene images or videos. The testing accuracy achieved is 95.26% when tested with 3969 testing images.

Item Type: Book Chapter
Additional Information: 5588/88883
Uncontrolled Keywords: convolutional neural networks, Adaboost algorithm, Haar-like features, skin de-tection, pornographic, image filtering, AlexNet.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Kulliyyah of Information and Communication Technology > Department of Information System
Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 30 Mar 2021 12:20
Last Modified: 11 May 2021 13:50
URI: http://irep.iium.edu.my/id/eprint/88883

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