Fingerprint Classification based on Orientaion Estimation

Manish Mathuria, Minaxi Cotia


The geometric characteristics of an object make it distinguishable. The objects present in the Environment known by their features and
properties. The fingerprint image as object may classify into sub classes based on minutiae structure. The minutiae structure may categorize as
ridge curves generated by the orientation estimation. The extracted curves are invariant to location, rotation and scaling. This classification
approach helps to manage fingerprints along their classes. This research provides a better collaboration of data mining based on classification.

Keywords: fingerprint recognition system; data mining; classification; orientation estimation; gradient based approach, sobel operator.

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