Department of Image Processing

Abstract: The Wienbibliothek im Rathaus, Vienna City Library, collected over 300 thousand posters scanned in high quality from the last 100 years. Browsing and searching in such a large dataset is beyond human power. Therefore, a project was set up in cooperation with the Technical University of Vienna to test the possibilities of automatic data annotation on a selected sample. One of the requirements was Content-based Image Retrieval - retrieving images based on their visual content. This thesis reviews these techniques that emerged over the last decades. We focus on simple techniques based on colour, texture, and shape, as well as more advanced algorithms using convolutional neural networks. We implement these methods and compare their retrieval effectiveness on particular image datasets. Finally, we describe the functionality of a developed web application.

Thesis: http://adamnovozamsky.com/file/2022_Diploma_Kostelecka.pdf