A modified robust and effective algorithm with mathematical calculation for minutiae detection

Abstract

Fingerprint classification and recognition is still an open and very challenging problem in real world applications. To achieve good minutiae extraction in fingerprints with varying quality, preprocessing in form of binarization and skeletonization is first applied on fingerprints before they are evaluated by the neural network. Extracted minutiae are then considered as a 2D point pattern problem and an efficient algorithm is used to determine the number of matching points between two point patterns. Performance of the developed system is evaluated on a database with fingerprints from different people and experimental results are presented.

Keywords: Algorithm, back propagation pattern, features, recognitions.