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--- |
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license: apache-2.0 |
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tags: |
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- finger-vein |
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- biometrics |
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- mobilenet |
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- siamese-network |
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- keras |
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- image-processing |
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--- |
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# 🩺 Finger Vein Feature Extractor using MobileNet |
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This pretrained model is designed for **finger vein recognition**. It uses a **MobileNet-based feature extractor** trained on finger images to extract deep biometric features. |
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## 🔧 How It Works: |
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- The model first extracts features from finger vein images using **MobileNet**. |
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- These features are then used to form **image pairs**. |
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- A **deep neural network** (e.g. Siamese) is trained on these pairs to learn a similarity metric. |
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- Finally, the system classifies whether two finger vein images belong to the **same person** or not. |
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## 📦 Use Cases: |
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- 🔐 Biometric authentication systems |
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- 🔍 Finger vein matching or verification |
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- 🧬 Medical/Forensic identification tasks |
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## 🖼️ Input: |
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- RGB finger vein image (resized to **224×224**) |
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- Normalized to [0, 1] |
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## 📤 Output: |
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- Feature vector (if using encoder only) |
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- Or: **Match / No-match** decision (in Siamese setup) |
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## 💾 Model Format: |
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- `model.keras` — Keras format for MobileNet feature extractor |
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## 💾 code Licence: |
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Alaerjan, A.S., Mostafa, A.M., Mahmoud, A.A. et al. Efficient multi-finger vein recognition using layer-wise progressive MobileNet fine-tuning and a Dense-Head Probabilistic Siamese Network. Sci Rep (2025). |
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https://doi.org/10.1038/s41598-025-32132-5 |
