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Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier
Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting n...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4068102/ https://www.ncbi.nlm.nih.gov/pubmed/25003153 http://dx.doi.org/10.1155/2014/753860 |
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author | Mustafa, Rashed Min, Yang Zhu, Dingju |
author_facet | Mustafa, Rashed Min, Yang Zhu, Dingju |
author_sort | Mustafa, Rashed |
collection | PubMed |
description | Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier. |
format | Online Article Text |
id | pubmed-4068102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-40681022014-07-07 Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier Mustafa, Rashed Min, Yang Zhu, Dingju ScientificWorldJournal Research Article Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier. Hindawi Publishing Corporation 2014 2014-06-05 /pmc/articles/PMC4068102/ /pubmed/25003153 http://dx.doi.org/10.1155/2014/753860 Text en Copyright © 2014 Rashed Mustafa et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Mustafa, Rashed Min, Yang Zhu, Dingju Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
title | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
title_full | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
title_fullStr | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
title_full_unstemmed | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
title_short | Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier |
title_sort | obscenity detection using haar-like features and gentle adaboost classifier |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4068102/ https://www.ncbi.nlm.nih.gov/pubmed/25003153 http://dx.doi.org/10.1155/2014/753860 |
work_keys_str_mv | AT mustafarashed obscenitydetectionusinghaarlikefeaturesandgentleadaboostclassifier AT minyang obscenitydetectionusinghaarlikefeaturesandgentleadaboostclassifier AT zhudingju obscenitydetectionusinghaarlikefeaturesandgentleadaboostclassifier |