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...

Full description

Bibliographic Details
Main Authors: Yongzhen Ke, Fan Qin, Weidong Min, Guiling Zhang
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/364501
id doaj-a5c907af47db4c6ca234ced4d19a9c96
record_format Article
spelling doaj-a5c907af47db4c6ca234ced4d19a9c962020-11-24T21:48:59ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/364501364501Exposing Image Forgery by Detecting Consistency of ShadowYongzhen Ke0Fan Qin1Weidong Min2Guiling Zhang3School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300387, ChinaDepartment of Logistics Management, Nankai University, Tianjin 300071, ChinaSchool of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300387, ChinaSchool of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300387, ChinaWe 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.http://dx.doi.org/10.1155/2014/364501
collection DOAJ
language English
format Article
sources DOAJ
author Yongzhen Ke
Fan Qin
Weidong Min
Guiling Zhang
spellingShingle Yongzhen Ke
Fan Qin
Weidong Min
Guiling Zhang
Exposing Image Forgery by Detecting Consistency of Shadow
The Scientific World Journal
author_facet Yongzhen Ke
Fan Qin
Weidong Min
Guiling Zhang
author_sort Yongzhen Ke
title Exposing Image Forgery by Detecting Consistency of Shadow
title_short 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_sort exposing image forgery by detecting consistency of shadow
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2014-01-01
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.
url http://dx.doi.org/10.1155/2014/364501
work_keys_str_mv AT yongzhenke exposingimageforgerybydetectingconsistencyofshadow
AT fanqin exposingimageforgerybydetectingconsistencyofshadow
AT weidongmin exposingimageforgerybydetectingconsistencyofshadow
AT guilingzhang exposingimageforgerybydetectingconsistencyofshadow
_version_ 1725890209247133696