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 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.
School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300387, China.
Yongzhen
Y
Ke
Department of Logistics Management, Nankai University, Tianjin 300071, China.
Fan
F
Qin
School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300387, China.
Weidong
W
Min
School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300387, China.
Guiling
G
Zhang
D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical