{'fraction_non_alphanumeric': 0.00993676603432701, 'fraction_numerical': 0.0, 'mean_word_length': 5.595238095238095, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Performance analysis of finger print sensors

Forensic Science is an art and science of a print made by an impression of ridges in the skin of a finger, often used for biometric identification in criminal investigation. The process of scanning a fingerprint image consists of sensor and a human interaction and the quality of image acquired is highly dependent on the fingerprint sensor used. This Paper emphasis on the technical details and performance comparison of various available fingerprint sensors and explores the future direction and system development that states using similar techniques for Chance or latent fingerprint enrollment. The study and experiments carried out indicates that the error occurred due to poor calibration causes a greater impact on the generated overall system output and serious usability issues with respect to handling of fingerprint sensors. Comparison table of various fingerprint enrollment sensors shows that Radio Frequency, Optical, Multi Spectrum Imaging, Micro-X-ray Fluorescence Elemental Imaging sensor techniques provides highest accuracy and compatibility.