Fingerprint Segmentation

In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.

The Björling 'Opera' : A children's Nursery Academy and an Italian Conservatory in Miniature

The aim in this chapter is to develop a deeper understanding about the informal Björling 'School' in Sweden. Contextually the example is related to the micro history of opera education contributing to the macro perspective illuminating a provincial example of the concept of domestic opera schooling. The specific focus was on Karl David Björling (1873-1926), the teaching parent of the Swedish tenor Jussi Björling (1911-1960) and his brothers Gösta and Olle.   The Björling family model of opera schooling belongs to the classical canon of domestic home education which was common during the epoch. The phenomenon is also within the field of opera singing an important reference to the historical context of the Nordic opera history of vocal education.   The uniqueness concerning the Björling School seems to be the rigorous and exceptionally early training. David Björling’s pedagogy was rooted in earlier German theories of musical upbringing. It's clear from his results that he was familiar with the neo-humanistic ideal on which reformed music education was based. Of a specific interest is the term Gesang als Unterricht as a concept for developing childrens musical and memorising capacities.   Conceptually the roots of the Björling model are in the eighteenth-century Romantic view of prodigies and their abilities. The extensive touring is connected to the promotion of wonder-children, and David Björling’s educational style to the conservative Master-pupil tradition.   David Björling's vocal ideal was a part of the contemporary debate about “The decadence of the singing art”, and seems to have its roots in an older Italian tradition. There are recurring similarities between his educational methods and the didactic principles of the Lamperti School: Enjoying a revival around the late 1800s and early 1900s, it has been called the natural or the national school. Nevertheless, through authentic experiences and gramophone recordings the Italian tenor Enrico Caruso became David Björling’s pedagogical role model.