Sokoto Coventry Fingerprint Dataset (SOCOFing)

Key Features of SOCOFing:

1. Diverse Subject Pool: The dataset includes fingerprints from 600 subjects, providing a rich variety of biometric data for research.
2. Detailed Labeling: Each fingerprint image is labeled with specific metadata, such as gender, hand (left or right), and finger name (e.g., thumb, index).
3. Synthetic Alterations: To facilitate robust testing and analysis, the dataset includes synthetically modified fingerprints. These alterations simulate real-world challenges in fingerprint recognition:
   • Obliteration: Partial removal or smudging of the fingerprint pattern.
   • Central Rotation: Rotation of the central part of the fingerprint to mimic common distortions.
   • Z-Cut: A synthetic cut through the fingerprint pattern to test resilience against physical damage.

Applications of SOCOFing:

• Biometric System Development: Researchers can use this dataset to develop and enhance fingerprint recognition algorithms.
• Security and Forensics: The dataset is valuable for studying the effects of alterations on fingerprint recognition, aiding in the development of more secure and reliable forensic tools.
• Academic Research: SOCOFing serves as a benchmark for academic research in biometrics, providing a standardized dataset for testing new methodologies and comparing results.