Open AccessPendeteksian Bagian Tubuh Manusia untuk Filter Pornografi dengan Metode Viola-Jones
Author(s) -
Benny Senjaya,
Alexander Agung Santoso Gunawan,
Jerry Pratama Hakim
Publication year - 2012
Publication title -
comtech/comtech
Language(s) - English
Resource type - Journals
eISSN - 2476-907X
pISSN - 2087-1244
DOI - 10.21512/comtech.v3i1.2447
Subject(s) - computer science , artificial intelligence , haar like features , computer vision , viola–jones object detection framework , boosting (machine learning) , pattern recognition (psychology) , viola , training set , face detection , facial recognition system , art , piano , art history
Information Technology does help people to get information promptly anytime and anywhere. Unfortunately, the information gathered from the Internet does not always come out positive. Some information can be destructive, such as porn images. To mitigate this problem, the study aims to create a desktop application that could detect parts of human body which can be expanded in the future to become an image filter application for pornography. The detection methodology in this study is Viola-Jones method which provides a complete framework for extracting and recognizing image features. A combination of Viola-Jones method with Haar-like features, integral image, boosting algorithm, and cascade classifier provide a robust detector for the application. First, several parts of the human body are chosen to be detected as the data training using the Viola-Jones method. Then, another set of images (similar body parts but different images) are run through the application to be recognized. The result shows 86.25% of successful detection. The failures are identified and show that the inputted data are completely different with the data training.