Professor Song invites you to attend the PhD dissertation defense of Di Wu

Abstract:

The use of fingerprints for personal identification has been around for thousands of years (first established in ancient China and India). Fingerprint identification is based on two basic premises that the fingerprint is unique to an individual and the basic characteristics such as ridge pattern do not change over time. Despite extensive research, there are still mathematical challenges in characterization of fingerprints, matching and compression. We develop a new mathematical model in the spatial domain for globally modeling loop pattern fingerprints. Although it is based on the well-known AM-FM (amplitude modulation and frequency modulation) image representation, the model is constructed by a global mathematical function for the continuous phase and it provides a flexible parametric model for loop pattern fingerprints. In sharp contrast to the existing methods, we estimate spatial parameters from the spectral domain by combining the exact values of frequencies with their orientations perpendicular to the fingerprint ridge flow. In addition, to compress fingerprint images and test background Gaussian white noise, we propose a new method based on periodogram spacings. We obtain the joint pdf of these m-dependent random variables at Fourier frequencies and derive the asymptotic distribution of the test statistic.

Cake and coffee will be served in GAB 472 following the event.