Latent fingerprint enhancement and matching using intuitionistic type-2 fuzzy. (24th April 2023)

• Record Type: Journal Article
• Authors: Mukhtar, Sayima; Dar, Mohsin Furkh; Kaur, Amandeep
• Is Part Of: International journal of artificial intelligence and soft computing. Volume 7:Number 4(2022)
• Page Start: 313
• Page End: 328
• Publication Date: 2023-04-24
• Subjects: latent fingerprint image -- fuzzy set -- similarity score -- Manhattan distance -- chi-square distance -- Earth mover's distance -- EMD; Artificial intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-4950

Abstract

Latent fingerprints are obtained from crime places by law enforcement and forensic agencies to identify the suspect. The latent fingerprints have vague ridge structures and various overlapping valley-based structures that result in low image quality. Furthermore, background noise, low contrast, and low information content make feature extraction difficult. To address these challenges, we propose a novel intuitionistic type-2 fuzzy relation for enhancing image quality. And to improve the matching score, a crossing number method is applied to extract minutiae points. The matching score is calculated using four different distance algorithms: Manhattan distance, Euclidean distance, Earth mover's distance, and chi-square distance. The proposed methodology is evaluated using three datasets IIITD, FVC-2004-1, and FVC-2004-2. The experimental results show that the proposed method yields satisfactory results, with the chi-square distance achieving the highest accuracy. The proposed method can be used by law enforcement and forensic agencies to reduce the workload.