A Combined Feature-Based Framework for Disguise and Spoofing Detection in Face Recognition Systems
Face recognition systems face two distinct, commonly-separated failure modes: spoofing, where an impostor presents a photograph or video of an authorized user, and disguise, where a legitimate user is rejected because their appearance differs from their enrolled template due to accessories, facial hair, illumination, or pose. This paper proposes and compares five combined feature-extraction and classification pipelines that address both problems within a single framework: PM (PCA and Minimum Euclidean Distance, MED), LPM (Local Binary Patterns with PCA and MED), HPM (Histogram of Oriented Gradients with PCA and MED), SM (Speeded-Up Robust Features with MED), and HM (Harris corner features...
| Authors | Sangiya Pararajasingham |
|---|---|
| Primary category | cs.CV |
| Published | 9 August 2026 |
| Last updated at source | 11 August 2026 |
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