The present work starts with an introduction of methods for three-dimensional curve skeletonization. Different kinds of historic and recent skeletonization approaches are analysed in detail. Later on, a state-of-the-art skeletonization algorithm is introduced. This algorithm deals as a basis for the own approach presented subsequently. After the description and definition of a new method improving the state-of-the-art algorithm, experiments are conducted to get appraisable results. Next, a ground truth is described which has been set up manually by humans. The human similarity evaluations are compared with the results of the automatic computer-based similarity measures provided by the own approach. For this comparison, standard evaluation criteria from the field of information retrieval have been used.
This bachelor thesis’s objective is to offer the reader insight into the discrete Fourier transform, the discrete cosine transform and the discrete Hadamard-Walsh transform in the context of image processing, and also to compare these transformations under various aspects. For this purpose the term of transformation, originated in linear algebra, will be explained and applied to image processing. Subsequently, the understanding of the Fourier transform will successively be built up and connected to the two remaining transforms. Finally, the transformations will be compared and their usefulness in relation to image processing will be explained.