Thinning Algorithms Analysis Minutiae Extraction with Terminations and Bifurcation Extraction from the Single-Pixeled Thinned Biometric Image

Thinning Algorithms Analysis Minutiae Extraction with Terminations and Bifurcation Extraction from the Single-Pixeled Thinned Biometric Image Bhargavi Devi Pottluarai Sharmila Kasinathan

Biometrics is the automatic identification of individuals based on physiological and behavioral characteristics. In today's technologically advanced digital world, it is regarded as the new digital key. There are two operating modes for biometric systems: identification and verification. The most popular biometric modalities are fingerprints, which are employed in many different industries and professions. Three distinct thinning methods are examined in this study. The proposed work looks into how thinning affects fingerprints, as well as minutiae extraction and texture feature analysis. To improve the quality of the fingerprints, thinning techniques such as Zhang- Suen's, Halls, and Guo Halls have been used. In terms of minutiae extraction, the thinning methods were compared. The minutiae points obtained were used to elaborate on the precision rate of fingerprints after processing. The simulations were run, and the experimental data was examined.
12 31 2022 12 31 2022 225 230 Crossmark v2.0 10.18280/CrossmarkPolicy www.iieta.org true 28 October 2022 1 December 2022 31 December 2022 http://iieta.org/sites/default/files/TEXT%20AND%20DATA%20MINING%20SERVICE%20AGREEMENT.pdf 10.18280/i2m.210603 https://www.iieta.org/journals/i2m/paper/10.18280/i2m.210603 https://www.iieta.org/journals/i2m/paper/10.18280/i2m.210603