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Exposing Image Forgery by Detecting Consistency of Shadow
We propose two tampered image detection methods based on consistency of shadow. The first method is based on texture consistency of shadow for the first kind of splicing image, in which the shadow as well as main body is copied and pasted from another image. The suspicious region including shadow an...
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/PMC3976866/ https://www.ncbi.nlm.nih.gov/pubmed/24757419 http://dx.doi.org/10.1155/2014/364501 |
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author | Ke, Yongzhen Qin, Fan Min, Weidong Zhang, Guiling |
author_facet | Ke, Yongzhen Qin, Fan Min, Weidong Zhang, Guiling |
author_sort | Ke, Yongzhen |
collection | PubMed |
description | We propose two tampered image detection methods based on consistency of shadow. The first method is based on texture consistency of shadow for the first kind of splicing image, in which the shadow as well as main body is copied and pasted from another image. The suspicious region including shadow and nonshadow is first selected. Then texture features of the shadow region and the nonshadow region are extracted. Last, correlation function is used to measure the similarity of the two texture features. By comparing the similarity, we can judge whether the image is tampered. Due to the failure in detecting the second kind of splicing image, in which main body, its shadow, and surrounding regions are copied and pasted from another image, another method based on strength of light source of shadows is proposed. The two suspicious shadow regions are first selected. Then an efficient method is used to estimate the strength of light source of shadow. Last, the similarity of strength of light source of two shadows is measured by correlation function. By combining the two methods, we can detect forged image with shadows. Experimental results demonstrate that the proposed methods are effective despite using simplified model compared with the existing methods. |
format | Online Article Text |
id | pubmed-3976866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-39768662014-04-22 Exposing Image Forgery by Detecting Consistency of Shadow Ke, Yongzhen Qin, Fan Min, Weidong Zhang, Guiling ScientificWorldJournal Research Article We propose two tampered image detection methods based on consistency of shadow. The first method is based on texture consistency of shadow for the first kind of splicing image, in which the shadow as well as main body is copied and pasted from another image. The suspicious region including shadow and nonshadow is first selected. Then texture features of the shadow region and the nonshadow region are extracted. Last, correlation function is used to measure the similarity of the two texture features. By comparing the similarity, we can judge whether the image is tampered. Due to the failure in detecting the second kind of splicing image, in which main body, its shadow, and surrounding regions are copied and pasted from another image, another method based on strength of light source of shadows is proposed. The two suspicious shadow regions are first selected. Then an efficient method is used to estimate the strength of light source of shadow. Last, the similarity of strength of light source of two shadows is measured by correlation function. By combining the two methods, we can detect forged image with shadows. Experimental results demonstrate that the proposed methods are effective despite using simplified model compared with the existing methods. Hindawi Publishing Corporation 2014-03-13 /pmc/articles/PMC3976866/ /pubmed/24757419 http://dx.doi.org/10.1155/2014/364501 Text en Copyright © 2014 Yongzhen Ke 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 Ke, Yongzhen Qin, Fan Min, Weidong Zhang, Guiling Exposing Image Forgery by Detecting Consistency of Shadow |
title | Exposing Image Forgery by Detecting Consistency of Shadow |
title_full | Exposing Image Forgery by Detecting Consistency of Shadow |
title_fullStr | Exposing Image Forgery by Detecting Consistency of Shadow |
title_full_unstemmed | Exposing Image Forgery by Detecting Consistency of Shadow |
title_short | Exposing Image Forgery by Detecting Consistency of Shadow |
title_sort | exposing image forgery by detecting consistency of shadow |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3976866/ https://www.ncbi.nlm.nih.gov/pubmed/24757419 http://dx.doi.org/10.1155/2014/364501 |
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