ADFF: Adaptive de‐morphing factor framework for restoring accomplice's facial image
Abstract Morphing attacks (MAs) pose a substantial security threat to the Automatic Border Control (ABC) system. While a few morphing attack detection (MAD) methods have been proposed, the face morphing accomplice's facial restoration has not received sufficient attention. Due to the inability...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-02-01
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| Series: | IET Image Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ipr2.12962 |
| _version_ | 1827364463436627968 |
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| author | Min Long Jun Zhou Le‐Bing Zhang Fei Peng Dengyong Zhang |
| author_facet | Min Long Jun Zhou Le‐Bing Zhang Fei Peng Dengyong Zhang |
| author_sort | Min Long |
| collection | DOAJ |
| description | Abstract Morphing attacks (MAs) pose a substantial security threat to the Automatic Border Control (ABC) system. While a few morphing attack detection (MAD) methods have been proposed, the face morphing accomplice's facial restoration has not received sufficient attention. Due to the inability to foresee the morphing factor used for a particular morphed image, selecting the appropriate de‐morphing factor becomes a challenging problem in the restoration of the accomplice's facial image. If the morphing factor cannot be chosen reasonably, achieving the desired restoration effect is difficult. Therefore, this paper presents an adaptive de‐morphing factor framework (ADFF) architecture for restoring the accomplice's facial image. By exploiting the morphed images stored in the electronic passport system and the real‐time captured criminal's images, ADFF can effectively restore the accomplice's facial image. Experimental results and analysis show that ADFF can significantly reduce the security threats of MAs on ABC. |
| first_indexed | 2024-03-08T08:09:28Z |
| format | Article |
| id | doaj.art-68626a71dbc54577b55572c13551f4d5 |
| institution | Directory Open Access Journal |
| issn | 1751-9659 1751-9667 |
| language | English |
| last_indexed | 2024-03-08T08:09:28Z |
| publishDate | 2024-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Image Processing |
| spelling | doaj.art-68626a71dbc54577b55572c13551f4d52024-02-02T09:31:01ZengWileyIET Image Processing1751-96591751-96672024-02-0118247048010.1049/ipr2.12962ADFF: Adaptive de‐morphing factor framework for restoring accomplice's facial imageMin Long0Jun Zhou1Le‐Bing Zhang2Fei Peng3Dengyong Zhang4School of Computer and Communication Engineering Changsha University of Science and Technology Changsha ChinaSchool of Computer and Communication Engineering Changsha University of Science and Technology Changsha ChinaSchool of Computer and Artificial Intelligence Huaihua University Huaihua ChinaInstitute of Artificial Intelligence and Blockchain Guangzhou University Guangzhou Guangdong ChinaSchool of Computer and Communication Engineering Changsha University of Science and Technology Changsha ChinaAbstract Morphing attacks (MAs) pose a substantial security threat to the Automatic Border Control (ABC) system. While a few morphing attack detection (MAD) methods have been proposed, the face morphing accomplice's facial restoration has not received sufficient attention. Due to the inability to foresee the morphing factor used for a particular morphed image, selecting the appropriate de‐morphing factor becomes a challenging problem in the restoration of the accomplice's facial image. If the morphing factor cannot be chosen reasonably, achieving the desired restoration effect is difficult. Therefore, this paper presents an adaptive de‐morphing factor framework (ADFF) architecture for restoring the accomplice's facial image. By exploiting the morphed images stored in the electronic passport system and the real‐time captured criminal's images, ADFF can effectively restore the accomplice's facial image. Experimental results and analysis show that ADFF can significantly reduce the security threats of MAs on ABC.https://doi.org/10.1049/ipr2.12962face recognitionimage forensics |
| spellingShingle | Min Long Jun Zhou Le‐Bing Zhang Fei Peng Dengyong Zhang ADFF: Adaptive de‐morphing factor framework for restoring accomplice's facial image IET Image Processing face recognition image forensics |
| title | ADFF: Adaptive de‐morphing factor framework for restoring accomplice's facial image |
| title_full | ADFF: Adaptive de‐morphing factor framework for restoring accomplice's facial image |
| title_fullStr | ADFF: Adaptive de‐morphing factor framework for restoring accomplice's facial image |
| title_full_unstemmed | ADFF: Adaptive de‐morphing factor framework for restoring accomplice's facial image |
| title_short | ADFF: Adaptive de‐morphing factor framework for restoring accomplice's facial image |
| title_sort | adff adaptive de morphing factor framework for restoring accomplice s facial image |
| topic | face recognition image forensics |
| url | https://doi.org/10.1049/ipr2.12962 |
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