Fingerprint Image

Fingerprint image analysis focuses on improving the accuracy and robustness of fingerprint-based biometric systems. Current research emphasizes enhancing image quality through techniques like deep learning-based denoising and enhancement (e.g., using U-Net architectures and wavelet transforms), improving fingerprint registration accuracy with novel neural network architectures (e.g., dual-branch networks), and developing methods to detect forged fingerprints generated by GANs. These advancements are crucial for enhancing security applications and addressing challenges like image degradation and demographic bias in fingerprint recognition systems.