Detection and Rectification of Distorted Fingerprints

Project Algorithm :

OpenCV, NumPy, Scikit-image, TensorFlow/Keras or PyTorch

Project Overview :

Fingerprint recognition is a widely used biometric authentication method in security systems. However, distorted or poor-quality fingerprints—caused by skin conditions, pressure variation, or sensor issues—can significantly degrade recognition accuracy. This project aims to automatically detect and rectify distorted fingerprints using image processing and machine learning techniques. The system includes modules for fingerprint enhancement, distortion detection, and rectification using convolutional neural networks (CNNs). By improving fingerprint quality before feature extraction and matching, the system enhances recognition performance and reduces false rejections, particularly in high-security or forensic applications.

Reference Video : -