Ing. Justýna Frommová

Ing. Justýna Frommová

Ing. Matěj Jech

Department of Applied Mathematics

This bachelor's thesis focuses on the detection and classification of defects in paper machine fabrics, which are in many ways similar to technical textiles. The main goal was to design and assemble an imaging system capable of collecting image data, collect data, and develop algorithms for automatic defect detection and classification. The thesis describes the design of the optical setup, selection of appropriate illumination, and camera system. It also presents image processing methods including filtering, transformations, and segmentation techniques used in the detection process. The outcome is a set of algorithms that can identify and distinguish specific types of defects with a certain level of accuracy. The final part of the thesis discusses the advantages and limitations of the proposed solution and outlines possibilities for future development.

Ing. Justýna Frommová

RNDr. Luděk Kleprlík, Ph.D.

Department of Applied Mathematics

This thesis focuses on the realistic and visually appealing fusion of vehicle images with selected backgrounds using 2D image processing techniques. To enhance the credibility of the image synthesis, reflections and shadows are generated for the vehicle. Particular attention is paid to parameterization and control of output properties such as shadow intensity, light source position, and appropriate reflection deformation. As part of the implementation, an algorithm was developed based on the Pixel Height method for modeling shadow geometry, enhanced with soft shadows, vehicle reflection using column rotation with smoothing via a moving average, and seamless foreground-background merging through alpha blending and edge blurring. Results are presented in both virtual environments and a real car showroom. The output of the algorithm demonstrates that the proposed solution is capable, except for few limitations, of producing aesthetically and technically acceptable results suitable for marketing purposes.

Ing. Justýna Frommová

Ing. Jitka Hrabáková, Ph.D.

Department of Applied Mathematics

The thesis designs and implements an algorithm capable of automatically creating video highlights from surf competitions. It also provides a dataset of 47 hours of annotated surf videos. A classification model utilizing MobileNet and LSTM binary classifies video frames as containing or not containing a surfer riding a wave. Signal smoothing methods are applied to its predictions and moments containing a riding surfer are selected. From these, output in the form of an edited highlights video is created. The algorithm achieves an adjusted accuracy of 97 % and correctly identifies 88 % of waves surfed. It completely misses only 1.5 % of surfed waves.