Implementation of modified polar complex moments-based fingerprint orientation estimation for effective segmentation

Segmentation is an important step in deciding the performance of fingerprint identification systems. In this paper, we present the modified polar complex moments MPCMs fingerprint orientation estimation algorithm, capable of describing the fingerprint flow structures including singular point regions in the fingerprint images effectively. To discard the background region of the low-quality fingerprint images, regularisation was employed. These algorithms are tested on various types of fingerprint images containing low-quality unrecoverable region and the results obtained from the proposed method were compared with those obtained from well-known gradient-based and PCMs methods. The proposed method was also used to study the contrast enhancement process with our previously developed modified histogram equalisation MHE based on adaptive inverse hyperbolic tangent AIHT method. The MPCMs method exhibits better segmentation than the traditional methods in both normal and low-contrast image segmentations, as evident from the estimated matching scores as well as ROC graph.

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