Volume 22 No 4 (2024)
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FACE MORPHING ATTACKS: GENERATION AND DETECTION TECHNIQUES
Dr. S. Venkata Achutha Rao,K Raghuram Yadav,B Aditya Rao,G saikiran reddy,S Srikanth
Abstract
The possibility of various illegal acts increases when face recognition and authentication systems fail.
Current face recognition systems can be easily compromised by various biometric techniques. This study
focuses on attack detection using morphing. An effective detection system is proposed that accounts for
differences in age, lighting, eyewear, and headgear. The system uses a deep learning-based feature
extractor in conjunction with a classifier. Additionally, we propose combining features and enhancing
images to improve detection accuracy.A multipurpose dataset, including Morph-2 and Morph-3 images
generated by advanced techniques with human participation, is also under development. Morph-3
images, due to their photorealistic quality, might be difficult to detect. Notably, no prior study has
considered Morph-3 images. Previous studies using free programs and code scripts produced morphs
that were less realistic than those generated by professional morphing software in a morph attack
scenario. To account for all possible variations, morphs are created using eight different face databases:
Celebrity2000, Extended Yale, FEI, FGNET, GT-DB, MULTI-PIE, FERET, and FRLL. After analyzing the
findings using various experimental settings, we can conclude that the proposed technique yields
encouraging results.
Keywords
Face recognition, morphing attack detection, deep learning, biometric security, image enhancement, multipurpose dataset, Morph-2, Morph-3, face databases.
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