Robust Image Forgery Detection Using Point Feature Analysis

被引：2

作者：

William, Youssef ^{[1
]}

Safwat, Sherine ^{[1
]}

Salem, Mohammed Abdel-Megeed ^{[1
,2
]}

机构：

[1] German Univ Cairo, Cairo, Egypt

[2] Ain Shams Univ, Cairo, Egypt

来源：

PROCEEDINGS OF THE 2019 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS) | 2019年

关键词：

Image Forgery; Copy-Move Forgery Detection; Image Splicing; SIFT; SURF; Support Vector Machine (SVM); benchmark dataset; CASIA datasets; Gray Level Co-occurrence Matrix (GLCM);

D O I：

10.15439/2019F227

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Day for day it becomes easier to temper digital images. Thus, people are in need of various forgery image detection. In this paper, we present forgery image detection techniques for two of the most common image tampering techniques; copy-move and splicing. We use match points technique after feature extraction process using SIFT and SURF. For splicing detection, we extracted the edges of the integral images of Y, C-b, and C-r, image components. GLCM is applied for each edge integral image and the feature vector is formed. The feature vector is then fed to a SVM classifier. For the copy-move, the results show that SURF feature extraction can be more efficient than SIFT, where we achieved 80% accuracy of detecting tempered images. On the other hand, processing the image in YCbCr color model is found to give promising results in splicing image detection. We have achieved 99% true positive rate for detecting splicing images.

引用

页码：373 / 380

页数：8

共 27 条

[11]

Hakimi F, 2015, 2015 2ND INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED ENGINEERING AND INNOVATION (KBEI), P1074, DOI 10.1109/KBEI.2015.7436195

[12]

Huynh TK, 2015, 2015 IEEE RIVF INTERNATIONAL CONFERENCE ON COMPUTING & COMMUNICATION TECHNOLOGIES - RESEARCH, INNOVATION, AND VISION FOR THE FUTURE (RIVF), P71, DOI 10.1109/RIVF.2015.7049877

[13] Exposing Postprocessed Copy-Paste Forgeries Through Transform-Invariant Features [J].

Kakar, Pravin ;

Sudha, N. .

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2012, 7 (03) :1018-1028

[14] Exposing Image Forgery by Detecting Consistency of Shadow [J].

Ke, Yongzhen ;

Qin, Fan ;

Min, Weidong ;

Zhang, Guiling .

SCIENTIFIC WORLD JOURNAL, 2014,

[15]

Lin S. D., 2011, 2011 4th International Congress on Image and Signal Processing (CISP 2011), P1086, DOI 10.1109/CISP.2011.6100366

[16]

Lin Shinfeng D, 2012, 2011 4 INT C IM SIGN, V2, P1086

[17]

Lindeberg T., 2012, SCHOLARPEDIA, V7, P10491

[18]

Pasquini Cecilia, 2015, VERIFICATION IMAGE I, P1, DOI [10.1109/ICMEW.2015.7169801, DOI 10.1109/ICMEW.2015.7169801]

[19] Handling multiple materials for exposure of digital forgeries using 2-D lighting environments [J].

Riess, Christian ;

Unberath, Mathias ;

Naderi, Farzad ;

Pfaller, Sven ;

Stamminger, Marc ;

Angelopoulou, Elli .

MULTIMEDIA TOOLS AND APPLICATIONS, 2017, 76 (04) :4747-4764

[20] Rotation Invariant Localization of Duplicated Image Regions Based on Zernike Moments [J].

Ryu, Seung-Jin ;

Kirchner, Matthias ;

Lee, Min-Jeong ;

Lee, Heung-Kyu .

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2013, 8 (08) :1355-1370

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