Academic Journal
Face morphing attack detection based on high-frequency features and progressive enhancement learning
| العنوان: | Face morphing attack detection based on high-frequency features and progressive enhancement learning |
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| المؤلفون: | Jia, Cheng-kun, Liu, Yong-chao, Chen, Ya-ling |
| المصدر: | Frontiers in Neurorobotics ; volume 17 ; ISSN 1662-5218 |
| بيانات النشر: | Frontiers Media SA |
| سنة النشر: | 2023 |
| المجموعة: | Frontiers (Publisher - via CrossRef) |
| الوصف: | Face morphing attacks have become increasingly complex, and existing methods exhibit certain limitations in capturing fine-grained texture and detail changes. To overcome these limitation, in this study, a detection method based on high-frequency features and progressive enhancement learning was proposed. Specifically, in this method, first, high-frequency information are extracted from the three color channels of the image to accurately capture the details and texture changes. Next, a progressive enhancement learning framework was designed to fuse high-frequency information with RGB information. This framework includes self-enhancement and interactive-enhancement modules that progressively enhance features to capture subtle morphing traces. Experiments conducted on the standard database and compared with nine classical technologies revealed that the proposed approach achieved excellent performance. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| DOI: | 10.3389/fnbot.2023.1182375 |
| DOI: | 10.3389/fnbot.2023.1182375/full |
| الاتاحة: | http://dx.doi.org/10.3389/fnbot.2023.1182375 https://www.frontiersin.org/articles/10.3389/fnbot.2023.1182375/full |
| Rights: | https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: | edsbas.C4260EEC |
| قاعدة البيانات: | BASE |
| DOI: | 10.3389/fnbot.2023.1182375 |
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