---
license: apache-2.0
tags:
- finger-vein
- biometrics
- mobilenet
- siamese-network
- keras
- image-processing
---

# 🩺 Finger Vein Feature Extractor using MobileNet

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.

## 🔧 How It Works:
- The model first extracts features from finger vein images using **MobileNet**.
- These features are then used to form **image pairs**.
- A **deep neural network** (e.g. Siamese) is trained on these pairs to learn a similarity metric.
- Finally, the system classifies whether two finger vein images belong to the **same person** or not.

## 📦 Use Cases:
- 🔐 Biometric authentication systems
- 🔍 Finger vein matching or verification
- 🧬 Medical/Forensic identification tasks

## 🖼️ Input:
- RGB finger vein image (resized to **224×224**)
- Normalized to [0, 1]

## 📤 Output:
- Feature vector (if using encoder only)
- Or: **Match / No-match** decision (in Siamese setup)

## 💾 Model Format:
- `model.keras` — Keras format for MobileNet feature extractor

## 💾 code Licence:
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). 
https://doi.org/10.1038/s41598-025-32132-5