Multi-region minutiae depth value-based efficient forged finger print analysis

• Published in: PloS one Vol. 18; no. 11; p. e0293249
• Main Authors: Baskar, M, Rajagopal, Renuka Devi, B. V. V. S., PRASAD, Babu, J. Chinna, Bartáková, Gabriela Pajtinková, Arulananth, T. S
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 16.11.2023; Public Library of Science (PLoS)
• Subjects: Algorithms; Bifurcations; Biometrics; Biometry; Classification; Datasets; Fingerprints; Fingers; Forecasts and trends; Forgery; Gabor filters; Image quality; Information technology; Methods; Regions; Security systems; India
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0293249

The application of biometrics has expanded the wings to many domains of application. However, various biometric features are being used in different security systems; the fingerprints have their own merits as it is more distinct. A different algorithm has been discussed earlier to improve the security and analysis of fingerprints to find forged ones, but it has a deficiency in expected performance. A multi-region minutiae depth value (MRMDV) based finger analysis algorithm has been presented to solve this issue. The image that is considered as input has been can be converted into noisy free with the help of median and Gabor filters. Further, the quality of the image is improved by sharpening the image. Second, the preprocessed image has been divided into many tiny images representing various regions. From the regional images, the features of ridge ends, ridge bifurcation, ridge enclosure, ridge dot, and ridge island. The multi-region minutiae depth value (MRMDV) has been computed based on the features which are extracted. The test image which has a similarity to the test image is estimated around MRMDV value towards forgery detection. The MRMDV approach produced noticeable results on forged fingerprint detection accuracy up to 98% with the least time complexity of 12 seconds.