Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/130269
Title: Image Forgery Localization via Integrating Tampering Possibility Maps
Authors: Haodong Li;Weiqi Luo;Xiaoqing Qiu;Jiwu Huang
Year: 2017
Publisher: IEEE
Abstract: Over the past decade, many efforts have been made in passive image forensics. Although it is able to detect tampered images at high accuracies based on some carefully designed mechanisms, localization of the tampered regions in a fake image still presents many challenges, especially when the type of tampering operation is unknown. Some researchers have realized that it is necessary to integrate different forensic approaches in order to obtain better localization performance. However, several important issues have not been comprehensively studied, for example, how to select and improve/readjust proper forensic approaches, and how to fuse the detection results of different forensic approaches to obtain good localization results. In this paper, we propose a framework to improve the performance of forgery localization via integrating tampering possibility maps. In the proposed framework, we first select and improve two existing forensic approaches, i.e., statistical feature-based detector and copy-move forgery detector, and then adjust their results to obtain tampering possibility maps. After investigating the properties of possibility maps and comparing various fusion schemes, we finally propose a simple yet very effective strategy to integrate the tampering possibility maps to obtain the final localization results. The extensive experiments show that the two improved approaches used in our framework significantly outperform the state-of-the-art techniques, and the proposed fusion results achieve the best F<sub>1</sub>-score in the IEEE IFS-TC Image Forensics Challenge.
URI: http://localhost/handle/Hannan/130269
volume: 12
issue: 5
More Information: 1240,
1252
Appears in Collections:2017

Files in This Item:
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7829291.pdf4.32 MBAdobe PDF
Title: Image Forgery Localization via Integrating Tampering Possibility Maps
Authors: Haodong Li;Weiqi Luo;Xiaoqing Qiu;Jiwu Huang
Year: 2017
Publisher: IEEE
Abstract: Over the past decade, many efforts have been made in passive image forensics. Although it is able to detect tampered images at high accuracies based on some carefully designed mechanisms, localization of the tampered regions in a fake image still presents many challenges, especially when the type of tampering operation is unknown. Some researchers have realized that it is necessary to integrate different forensic approaches in order to obtain better localization performance. However, several important issues have not been comprehensively studied, for example, how to select and improve/readjust proper forensic approaches, and how to fuse the detection results of different forensic approaches to obtain good localization results. In this paper, we propose a framework to improve the performance of forgery localization via integrating tampering possibility maps. In the proposed framework, we first select and improve two existing forensic approaches, i.e., statistical feature-based detector and copy-move forgery detector, and then adjust their results to obtain tampering possibility maps. After investigating the properties of possibility maps and comparing various fusion schemes, we finally propose a simple yet very effective strategy to integrate the tampering possibility maps to obtain the final localization results. The extensive experiments show that the two improved approaches used in our framework significantly outperform the state-of-the-art techniques, and the proposed fusion results achieve the best F<sub>1</sub>-score in the IEEE IFS-TC Image Forensics Challenge.
URI: http://localhost/handle/Hannan/130269
volume: 12
issue: 5
More Information: 1240,
1252
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7829291.pdf4.32 MBAdobe PDF
Title: Image Forgery Localization via Integrating Tampering Possibility Maps
Authors: Haodong Li;Weiqi Luo;Xiaoqing Qiu;Jiwu Huang
Year: 2017
Publisher: IEEE
Abstract: Over the past decade, many efforts have been made in passive image forensics. Although it is able to detect tampered images at high accuracies based on some carefully designed mechanisms, localization of the tampered regions in a fake image still presents many challenges, especially when the type of tampering operation is unknown. Some researchers have realized that it is necessary to integrate different forensic approaches in order to obtain better localization performance. However, several important issues have not been comprehensively studied, for example, how to select and improve/readjust proper forensic approaches, and how to fuse the detection results of different forensic approaches to obtain good localization results. In this paper, we propose a framework to improve the performance of forgery localization via integrating tampering possibility maps. In the proposed framework, we first select and improve two existing forensic approaches, i.e., statistical feature-based detector and copy-move forgery detector, and then adjust their results to obtain tampering possibility maps. After investigating the properties of possibility maps and comparing various fusion schemes, we finally propose a simple yet very effective strategy to integrate the tampering possibility maps to obtain the final localization results. The extensive experiments show that the two improved approaches used in our framework significantly outperform the state-of-the-art techniques, and the proposed fusion results achieve the best F<sub>1</sub>-score in the IEEE IFS-TC Image Forensics Challenge.
URI: http://localhost/handle/Hannan/130269
volume: 12
issue: 5
More Information: 1240,
1252
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7829291.pdf4.32 MBAdobe PDF