An algorithm for nudity detection

This paper presents an algorithm for detecting nudity in color images. A skin color distribution model based on the RGB, Normalized RGB, and HSV color spaces is constructed using correlation and linear regression. The skin color model is used to identify and locate skin regions in an image. These re...

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Main Author: Ap-apid, Rigan P.
Format: text
Published: Animo Repository 2005
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/12587
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-144872024-05-28T07:56:11Z An algorithm for nudity detection Ap-apid, Rigan P. This paper presents an algorithm for detecting nudity in color images. A skin color distribution model based on the RGB, Normalized RGB, and HSV color spaces is constructed using correlation and linear regression. The skin color model is used to identify and locate skin regions in an image. These regions are analyzed for clues indicating nudity or nonnudity 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. 2005-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/12587 Faculty Research Work Animo Repository Pornography Nudity Image processing Regression analysis Theory and Algorithms
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
topic Pornography
Nudity
Image processing
Regression analysis
Theory and Algorithms
spellingShingle Pornography
Nudity
Image processing
Regression analysis
Theory and Algorithms
Ap-apid, Rigan P.
An algorithm for nudity detection
description This paper presents an algorithm for detecting nudity in color images. A skin color distribution model based on the RGB, Normalized RGB, and HSV color spaces is constructed using correlation and linear regression. The skin color model is used to identify and locate skin regions in an image. These regions are analyzed for clues indicating nudity or nonnudity 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 An algorithm for nudity detection
title_short An algorithm for nudity detection
title_full An algorithm for nudity detection
title_fullStr An algorithm for nudity detection
title_full_unstemmed An algorithm for nudity detection
title_sort algorithm for nudity detection
publisher Animo Repository
publishDate 2005
url https://animorepository.dlsu.edu.ph/faculty_research/12587
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