A Conceptual Study on Fingerprint Thinning Process based on Edge Prediction

Biometric recognition encompasses numerous modern strategies. Among them, fingerprint reputation is taken into consideration to be the most effective approach for utmost security authentication. As industrial incentives boom, many new technologies for user identity are being advanced, each with its very own strengths and weaknesses and a potential area of interest marketplace. Fingerprint matching consists of a different process like filtering or preprocessing, binarisation, thinning or skeletonisation, postprocessing, feature extraction, and matching. Out of these fingerprint thinning or skeletonisation is one of the important processes in fingerprint identification or verification systems. Fingerprint thinning or skeletonisation is the manner or technique of lowering the thickness of every line of a fingerprint pattern or ridge pattern to just a single pixel width. After extracting the minutiae from the improved, binarised and thinned image some post-processing is carried out on this final fingerprint image to take away any spurious minutiae. The techniques on this class are of types–crossing number based and morphology-based totally. In this paper even though a new method for thinning is not proposed but a real attempt is made to explain the Edge prediction based thinning process. The Edge Prediction based Skelton formation is totally based on the conditional thinning set of rules, which is used to carry out thinning. The Edge Prediction based thinning process is explained with the help of workflow, algorithm, and flowchart