Work

Review on Advancements in Fingerprint Analysis: From Historical Developments to Modern Deep Learning Applications

Year: 2026

Type: article

Abstract: The evolution of fingerprint analysis traces its roots from the early studies by Marcello Malpighi in the 17th century to its crucial role in modern forensic science. Over time, significant advancements in technology, particularly in image processing and machine learning, have revolutionized fingerprint analysis. This paper explores the historical development of fingerprint analysis, the importance of digital processing, and the role of Automated Fingerprint Recognition Systems (AFRS). It further delves into the significance of noise removal and image-denoising techniques, highlighting the impact of state-of-the-art methods such as Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs). The integration of deep learning techniques has significantly enhanced fingerprint-matching accuracy, speed, and reliability, marking a pivotal shift in forensic investigations and biometric authentication.

Source: International Journal of Innovative Science and Research Technology (IJISRT)

DOI: 10.38124/ijisrt/26oct1428

Authors: Phebe Tryphena I., Priyadharshi Pradhan, G. Jayanthi, S. Raghuraghavendra

Institution: Sri Ramachandra Institute of Higher Education and Research

Language: English

Topic: Biometric Identification and Security

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W7225461251

FWCI:

Cites: 28

Cited by:

Related to: 10