Nudity detection in color images

The proliferation of nude images is a problem that affects families, the workplace, and society in general. To address this problem, many studies in visual content security are being done. However, the current state of technology is still crude, yielding inexact results at the cost of computing powe...

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Main Author: Ap-Apid, Rigan P.
Format: text
Language:English
Published: Animo Repository 2004
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Online Access:https://animorepository.dlsu.edu.ph/etd_masteral/3227
https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10065/viewcontent/CDTG003796_P.pdf
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Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etd_masteral-10065
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spelling oai:animorepository.dlsu.edu.ph:etd_masteral-100652022-08-24T16:15:06Z Nudity detection in color images Ap-Apid, Rigan P. The proliferation of nude images is a problem that affects families, the workplace, and society in general. To address this problem, many studies in visual content security are being done. However, the current state of technology is still crude, yielding inexact results at the cost of computing power. Thus, new methods for nudity detection are being sought. In this study, a new algorithm for detecting nudity in color images is developed. A skin color distribution model is constructed using correlation and linear regression. This model is used to identify and locate skin regions in an image. These regions are analyzed for clues indicating nudity or non-nudity such as their sizes and relative distances from each other. Based on these clues and the percentage of skin in the image, an image is classified nude or non-nude. The skin color distribution model performs with 96.29% recall and 6.76% false positive rate on a test set consisting of 2,303,824 manually labeled skin pixels and 24,285,952 manually labeled non-skin pixels. The Nudity Detection Algorithm is able to detect nudity with a 94.77% recall and a false positive rate of 5.04% on a set of images consisting of 421 nude images and 635 non-nude images. 2004-01-01T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etd_masteral/3227 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10065/viewcontent/CDTG003796_P.pdf Master's Theses English Animo Repository Image processing Computer vision Nudity Nude in art Human figure in art--Pictorial works Photography of the nude Computer Sciences
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Image processing
Computer vision
Nudity
Nude in art
Human figure in art--Pictorial works
Photography of the nude
Computer Sciences
spellingShingle Image processing
Computer vision
Nudity
Nude in art
Human figure in art--Pictorial works
Photography of the nude
Computer Sciences
Ap-Apid, Rigan P.
Nudity detection in color images
description The proliferation of nude images is a problem that affects families, the workplace, and society in general. To address this problem, many studies in visual content security are being done. However, the current state of technology is still crude, yielding inexact results at the cost of computing power. Thus, new methods for nudity detection are being sought. In this study, a new algorithm for detecting nudity in color images is developed. A skin color distribution model is constructed using correlation and linear regression. This model is used to identify and locate skin regions in an image. These regions are analyzed for clues indicating nudity or non-nudity such as their sizes and relative distances from each other. Based on these clues and the percentage of skin in the image, an image is classified nude or non-nude. The skin color distribution model performs with 96.29% recall and 6.76% false positive rate on a test set consisting of 2,303,824 manually labeled skin pixels and 24,285,952 manually labeled non-skin pixels. The Nudity Detection Algorithm is able to detect nudity with a 94.77% recall and a false positive rate of 5.04% on a set of images consisting of 421 nude images and 635 non-nude images.
format text
author Ap-Apid, Rigan P.
author_facet Ap-Apid, Rigan P.
author_sort Ap-Apid, Rigan P.
title Nudity detection in color images
title_short Nudity detection in color images
title_full Nudity detection in color images
title_fullStr Nudity detection in color images
title_full_unstemmed Nudity detection in color images
title_sort nudity detection in color images
publisher Animo Repository
publishDate 2004
url https://animorepository.dlsu.edu.ph/etd_masteral/3227
https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10065/viewcontent/CDTG003796_P.pdf
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