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Fingerprint Embedding ResNet18
A prototype fingerprint embedding model based on pretrained ResNet18.
Model Details
- Architecture: ResNet18
- Input Size: 224 × 224
- Input: Grayscale fingerprint converted to 3 channels
- Embedding Size: 512
- Output: L2-normalized embedding
- Similarity Metric: Cosine Similarity
Current Test Results
- Same Fingerprint Similarity: 0.9128
- Different Fingerprint Similarity: 0.8878
Pipeline
Fingerprint Image → Preprocessing → ResNet18 → 512-D Embedding → L2 Normalization → Cosine Similarity
Status
This model is currently a prototype.
The ResNet18 backbone has not yet been trained specifically for fingerprint recognition.
Future Work
- Train on a fingerprint dataset
- Siamese Network
- Contrastive / Triplet Loss
- Improve embedding separation
- FAR / FRR / EER evaluation
- Export to ONNX
Warning
Do not use this prototype for production biometric authentication.
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