<![CDATA[Fingerprint recognition is a popular biometric technology due to its unique properties and high accuracy rate. Fingerprint recognition systems generally use fingerprint image representations, such as grayscale images, phase images, skeleton images, and minutiae. In this research, fingerprint image pre-processing is performed using Gaussian Blur, Median Blur, Thresholding, Otsu Thresholding, Thinning with Guo-Hall algorithm, and Minutiae Detection. Minutiae detection produces 426 termination points and 459 bifurcation points. The results of the pre-processing and minutiae detection were then used for minutiae matching on 5 different images. Minutiae matching produces varying degrees of similarity with a high level of accuracy, reaching an average accuracy of 88.80%.]]>
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